dennisthiessenandClaude Opus 5
a0f844c143
RUAG C5I - AI Engineer C5I (Thun, app ID 18027): SUBMITTED 2026-08-27. Evidence Fit 74/100, fit class Stretch, title-capability hard gate FAIL (R1 build/operate the AI-LLM platform and R2 in-house LLM/retrieval are Adjacent, not Direct) - all knowingly accepted under the user's explicit Phase 0 override. Consumes the cohort's sole Stretch slot: cohort is now 6/10, Stretch 1/1. Critique ran twice. Round 1 scored the documents 85/100 and raised three Tier 1 items; Round 2, after the fixes, scores 93/100 with truth and provenance 24/25 and zero Tier 1 findings. Evidence Fit did not move and was not allowed to: PP-3 is a personal project and cannot convert an Adjacent title-capability into a Direct one. Documents (.tex is the deliverable; PDFs are gitignored): - resume 2pp/13 bullets, letter 1pp/295 words, both validators PASS - headline is now the canonical title "Staff Data, Analytics & AI Engineer", which puts the req's own word above the fold - PP-3 added as a Projekte section - the only current Linux/hardening evidence, since BS-6 ended Dec 2022 - the letter names the AI-platform gap in one sentence, then connects SW-5 to C5I's stated DevSecOps model - "governte" -> "governance-konforme"; JD term coverage 18/22 -> 22/22 claimable, with all six gap terms still correctly absent Two defects found and fixed that the first critique missed: - the resume never loaded babel, so a German document was hyphenated with English patterns (Hal-bleiterfertigung, Tran-skription). Fixed with babel[ngerman] plus a Transkription exception; this also cleared an overfull box. Check this on every future German package - resume_template.tex likely has the same omission. - IBM AI Engineering had no primary-source record. Certificate read directly (IBM via Coursera, 4 Jun 2020, verify 3ZBZFVAL6A34), recorded as entry #8; it also proves PyTorch, now evidence: certification. Also included: the submitted Kdo Cy DevOps Engineer III package, the Capgemini omit rule promoted into config.md, BW-1 canonicalized in experience_bundeswehr.md, and a scout.py comment correcting the telenorgroup slug from "near-empty" to a claimed board serving stale phantom listings that DEMO_TITLES would not catch. Compensation, PSP/project eligibility and role level were never resolved before sending and are now live screening topics. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01JMcHCsTKWvVzqyLChF5ckk
711 lines
29 KiB
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711 lines
29 KiB
JSON
{
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"schema_version": 1,
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"last_verified": "2026-08-27",
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"authority": {
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"description": "Machine-readable source of truth for all future application documents.",
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"precedence": [
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"canonical claims",
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"config corrections",
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"verified references",
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"experience files",
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"bundles"
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],
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"raw_extractions_are_immutable": true,
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"historical_outputs_are_never_sources": true
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},
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"identity": {
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"name": "Dennis Thiessen",
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"degree_suffix": "M.Eng.",
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"email": "dennis@thiessen.io",
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"phone": "+41 795 955 585",
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"location": "Bern, Switzerland",
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"linkedin": "linkedin.com/in/dennis-thiessen",
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"citizenship": "German citizen (EU)",
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"swiss_permit": "B residence permit",
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"swiss_work_authorization": "Authorized to work in Switzerland; no visa or employer sponsorship required",
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"work_authorization_source": "User-confirmed 2026-07-27",
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"resume_usage": "Work authorization is optional in the header; mention the B permit or no-sponsorship status when it resolves recruiter uncertainty or the application asks for it",
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"languages": {
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"German": "native",
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"English": "fluent",
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"Norwegian": "basic",
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"Russian": "basic"
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},
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"forbidden_personal_data": [
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"date of birth",
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"marital status",
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"gender",
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"children"
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]
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},
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"education": [
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{
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"id": "EDU-MENG",
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"degree": "M.Eng. Computer Aided Engineering",
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"display_focus": "Software Design & Engineering",
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"institution": "Universitat der Bundeswehr Munchen",
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"start": "2012-04",
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"end": "2013-10",
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"thesis_institution": "Tongji University, Shanghai",
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"thesis_title": "Development of a Web-Based Remote Fault Diagnosis System",
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"final_grade": "1.6 (German scale, 1.0 best / 4.0 lowest pass) -- user-confirmed 2026-08-26",
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"final_grade_us_4pt": "3.4 -- modified Bavarian formula, US = 1 + 3*(4.0-G)/(4.0-1.0), which simplifies to 5.0 - G. Use ONLY when a form demands a 4.0-scale GPA; always state the German scale alongside it. Never present as a natively-awarded GPA.",
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"thesis_grade": "1.0",
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"thesis_relative_grade": "ECTS grade B; official certificate on file. B is formally the next 25% after the top 10%, i.e. the 10-35% band -- so the correct and safe phrasing is 'top 35%' (user-confirmed 2026-08-26). Do NOT write 'top 30%' or 'top 25%': B is a band, not a point, and narrowing it overstates the standing. The original 'top 35%' in this record was correct; a briefly-considered 30% was the error.",
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"thesis_methods": "Verified against the thesis PDF 2026-08-02. Domain: vibration-based condition monitoring of CNC machine tools (piezoelectric accelerometers on spindle, tool rest, lathe body). Features: speed, load and the dimensionless waveform, peak, pulse, margin and kurtosis indices. Surveyed CBR, PSO, RBR and ANN; SELECTED a hybrid of rule-based reasoning (interpretable thresholds) plus a 7-10-3 feed-forward ANN (faultstates green/yellow/red) to handle noisy data that static rules cannot classify. Extensible plug-in architecture for swappable diagnosis methods and data collectors. Java/GWT client-server on MySQL. Evaluation measured throughput and latency, NOT model accuracy: the pipeline sustained ~500 samples/s against tri-axial vibration sensors delivering 72.9 kSPS, so the thesis concluded data reduction, filtering or batch scheduling is required for real-time use.",
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"thesis_limits": "PSO was SURVEYED ONLY and NOT used in the implementation -- never claim it as an applied method. No real operational data: training data came from a cited thesis, test data was modified plus a random generator. No model-accuracy figures exist. Back-propagation retraining was listed as future work, not implemented. Frame as a methods prototype/framework, never as a validated production predictive-maintenance system.",
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"transcripts_language": "English-language originals available for B.Eng. and M.Eng."
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},
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{
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"id": "EDU-BENG",
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"degree": "B.Eng. Information and Telecommunication Technologies",
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"institution": "Universitat der Bundeswehr Munchen",
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"start": "2009-10",
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"end": "2012-10",
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"final_grade": "2.4 (German scale, 1.0 best / 4.0 lowest pass) -- user-confirmed 2026-08-26",
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"final_grade_us_4pt": "2.6 -- modified Bavarian formula (5.0 - G). Supply ONLY when a form requires a bachelor GPA; leave blank where optional. Always state the German scale alongside it, because the conversion makes German degrees read weaker to a US audience than they are: 2.4 is a solid 'gut'. Never present as a natively-awarded GPA.",
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"grade_output_rule": "Neither degree grade goes on the resume or in a cover letter by default. Industry resumes omit grades; the M.Eng. thesis grade 1.0 is the only figure worth surfacing, and only where academic performance is genuinely valued. These fields exist for application-form GPA questions and credential checks."
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}
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],
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"employment": [
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{
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"id": "SWISSCOM",
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"employer": "Swisscom (Schweiz) AG",
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"location": "Bern, Switzerland",
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"display_title": "Staff Data, Analytics & AI Engineer",
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"start": "2023-10",
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"end": "present",
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"title_history": [
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{
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"title": "Senior Data, Analytics & AI Engineer",
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"start": "2023-10",
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"end": "2025-04"
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},
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{
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"title": "Staff Data, Analytics & AI Engineer",
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"start": "2025-04",
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"end": "present"
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}
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]
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},
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{
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"id": "BOSCH",
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"employer": "Robert Bosch Semiconductor Manufacturing Dresden GmbH",
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"location": "Dresden, Germany",
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"official_title": "Engineer / Senior Engineer, Data Analysis",
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"display_title": "Senior Data Engineer, Data Analysis",
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"display_title_note": "experience_bosch.md sanctions title flexibility for this role: '(Senior) Data Engineer' or '(Senior) Data Analysis Engineer' depending on the JD. 'Senior Data Engineer, Data Analysis' is the user's own preferred wording, confirmed 2026-08-27. official_title stays the formal combined string on the Zeugnis.",
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"start": "2020-02",
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"end": "2022-12",
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"title_history": [
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{"title": "Data Engineer, Data Analysis", "start": "2020-02", "end": "2021-01"},
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{"title": "Senior Data Engineer, Data Analysis", "start": "2021-01", "end": "2022-12"}
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],
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"title_history_source": "LinkedIn-confirmed, recorded in experience_bosch.md; user-confirmed 2026-08-27 while reviewing the RUAG C5I resume. Added because claims.json previously carried only the combined official_title with no promotion date, which made a Swisscom-style 'Beforderung <date>' line unwritable from the canonical file alone."
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},
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{
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"id": "FRAUNHOFER",
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"employer": "Fraunhofer-Center for Maritime Logistics and Services CML",
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"location": "Hamburg, Germany",
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"official_title": "Wissenschaftlicher Mitarbeiter",
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"display_title": "Research Software Engineer",
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"start": "2018-09",
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"end": "2019-10"
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},
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{
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"id": "VIZRT",
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"employer": "Vizrt",
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"location": "Bergen, Norway",
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"official_title": "Test Automation Engineer",
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"display_title": "Test Automation / DevOps Engineer",
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"start": "2017-07",
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"end": "2018-05"
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},
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{
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"id": "GENERALI",
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"employer": "Generali Deutschland Informatik Services GmbH",
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"location": "Hamburg, Germany",
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"display_title": "IT Consultant",
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"start": "2015-05",
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"end": "2017-06"
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},
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{
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"id": "CAPGEMINI",
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"employer": "Capgemini Deutschland GmbH",
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"location": "Hamburg, Germany",
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"display_title": "Software Engineer",
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"start": "2014-11",
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"end": "2015-05"
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},
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{
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"id": "BUNDESWEHR",
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"employer": "Bundeswehr (German Armed Forces)",
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"location": "Germany",
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"display_title": "Officer Candidate / Officer (Second Lieutenant at separation)",
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"start": "2008-07",
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"end": "2014-11",
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"source": "User confirmation 2026-07-10; thiessen_linkedin_profile.md",
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"last_verified": "2026-08-27"
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}
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],
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"claims": [
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{
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"id": "SW-1",
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"scope": "Primary engineer for pipelines in owned Fulfillment and Product Analysis domains; contributor to the wider company migration.",
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"allowed_verbs": [
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"migrated",
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"implemented",
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"contributed"
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],
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"forbidden": [
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"led the migration of the legacy warehouse",
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"sole technical lead",
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"migrated the company warehouse",
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"owned the full migration"
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],
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"metrics": "unverified"
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},
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{
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"id": "SW-2",
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"scope": "Component Owner for business-critical Fulfillment ETL pipelines, including operation, data quality, governance, incidents and on-call obligations.",
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"allowed_verbs": [
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"own",
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"operate",
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"maintain",
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"serve"
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],
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"metrics": "unverified"
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},
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{
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"id": "SW-3",
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"scope": "Build and operate Python data applications on Kubernetes with GitLab CI/CD within the team environment.",
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"allowed_verbs": [
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"build",
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"deploy",
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"operate"
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],
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"metrics": "unverified"
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},
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{
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"id": "SW-4",
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"scope": "Deliver data products, dashboards and analyses with internal B2B stakeholders and product owners; not external consulting or strategic-account delivery.",
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"allowed_verbs": [
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"deliver",
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"translate",
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"partner",
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"support"
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],
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"forbidden": [
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"customer-embedded delivery",
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"strategic customer delivery",
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"C-suite advisor"
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],
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"metrics": "unverified"
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},
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{
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"id": "SW-5",
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"scope": "Mandatory rotating team Security Champion role for 2025/2026 only; not an award, certification or multi-year distinction.",
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"allowed_verbs": [
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"serve"
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],
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"forbidden": [
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"3 consecutive years",
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"2023-2026",
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"Security Champion x3",
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"owning DevSecOps compliance"
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],
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"metrics": "100 hours of training and an assessment are source-backed; use only when relevant"
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},
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{
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"id": "SW-6",
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"scope": "Hands-on PySpark use at Swisscom; scale and performance metrics are not verified.",
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"allowed_verbs": [
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"use",
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"develop",
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"process"
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],
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"metrics": "unverified"
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},
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{
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"id": "SW-7",
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"scope": "Build governed data products and onboard sources within Swisscom's company-wide Data Mesh; never claim ownership or construction of the shared mesh/platform. Atlassian Compass is the metadata/catalogue platform used for data-product metadata and lineage (user-confirmed 2026-07-29); Dennis uses it as a practitioner and does not administer or own the tooling.",
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"allowed_verbs": [
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"build",
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"model",
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"onboard",
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"contribute",
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"document",
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"maintain"
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],
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"forbidden": [
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"built a Data Mesh",
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"built the Data Mesh",
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"built AWS Data Mesh",
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"own the AWS data platform",
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"own the data platform",
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"own Atlassian Compass",
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"administered Compass",
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"rolled out Compass"
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],
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"metrics": "unverified"
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},
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{
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"id": "SW-8",
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"scope": "Configured domain-grounded LLM assistants in a Swisscom-owned web interface by selecting available models and supplying curated knowledge. Separate exposure includes LiteLLM API use, custom GPTs, Copilot and Kiro.",
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"allowed_verbs": [
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"configured",
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"used",
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"integrated"
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],
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"forbidden": [
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"built production LLM systems",
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"deployed LLM systems",
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"built LangChain",
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"agent orchestration",
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"formal LLM evaluation",
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"fine-tuned models"
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],
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"metrics": "unverified"
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},
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{
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"id": "BS-1",
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"scope": "Designed and executed integration of containerized ML inference into a 24/7 semiconductor production environment; model-development ownership is not established. Toolchain includes Docker, Kubernetes and Ansible - Ansible use at Bosch was intensive (user-confirmed 2026-08-27) and extended to configuration management and infrastructure automation beyond this single integration, making it standalone Infrastructure-as-Code evidence.",
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"allowed_verbs": [
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"integrated",
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"containerized",
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"deployed",
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"orchestrated"
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],
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"forbidden": [
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"trained the image classification model",
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"owned the full ML lifecycle"
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],
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"metrics": "qualitative reduction in manual classification is source-backed; exact amount unverified"
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},
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{
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"id": "BS-2",
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"scope": "Developed data services in Python, Java and C# over Oracle and Hadoop/Impala for internal analysis teams. Data types worked on (user-confirmed 2026-08-02): semiconductor fab sensor and process data -- defect management records, wafer inspection images, and electrical parameters from Process Control Monitoring (PCM). Relevant as genuine industrial sensor/asset-data experience.",
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"allowed_verbs": [
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"developed",
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"built"
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],
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"metrics": "unverified"
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},
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{
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"id": "BS-3",
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"scope": "Confirmed Application Owner responsibilities for analytics applications and upstream pipelines, including SLOs, vendors, training and documentation.",
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"allowed_verbs": [
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"served",
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"owned",
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"managed",
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"defined"
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],
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"metrics": "unverified"
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},
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{
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"id": "BS-4",
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"scope": "Built an ELK/Kafka anomaly-detection proof of concept and monitoring; not a company-wide observability platform.",
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"allowed_verbs": [
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"built",
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"implemented",
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"validated"
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],
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"forbidden": [
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"built the observability platform",
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"enterprise observability platform"
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],
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"metrics": "unverified"
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},
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{
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"id": "BS-5",
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"scope": "Co-owned the TIBCO Spotfire environment, built C# extensions and co-presented at TIBCO Analytics Forum 2022.",
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"allowed_verbs": [
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"co-owned",
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"built",
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"co-presented"
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],
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"metrics": "unverified"
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},
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{
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"id": "BS-6",
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"scope": "Administered and automated the Linux server estate underpinning fab analytics and ML workloads at Bosch (2020-2022): ML platform hosts, Docker hosts, backend services and the Ansible control path. Developed Ansible extensions, including a credential plugin that retrieved secrets from a password keystore and cached them locally to cut lookup volume and improve scalability and performance. Playbooks were version-controlled in Git and executed push-style from Jenkins/GitLab pipelines. User-confirmed 2026-08-27.",
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"allowed_verbs": [
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"administered",
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"automated",
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"developed",
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"extended",
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"operated",
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"built"
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],
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"forbidden": [
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"owned the fab's infrastructure",
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"ran the datacenter",
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"SRE role or title",
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"GitOps",
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"any server-count, uptime, SLA or scale figure - none is verified"
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],
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"metrics": "none verified; the credential-caching plugin reduced keystore lookups, amount unquantified"
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},
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{
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"id": "FC-1",
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"scope": "Set up Jenkins CI/CD and contributed to SCEDAS development and maintenance.",
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"allowed_verbs": [
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"set up",
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"developed",
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"maintained"
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],
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"metrics": "unverified"
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},
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{
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"id": "FC-2",
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"scope": "Contributed ML/NLP components to ARTUS; no publication or model-training ownership.",
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"allowed_verbs": [
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"contributed",
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"implemented",
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"supported"
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],
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"forbidden": [
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"led ARTUS",
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"trained the speech model"
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],
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"metrics": "unverified"
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},
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{
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"id": "FC-3",
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"scope": "Developed containerized microservices for the MISSION research platform.",
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"allowed_verbs": [
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"developed",
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"built"
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],
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"metrics": "unverified"
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},
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{
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"id": "VZ-1",
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"scope": "Contributed Python and C++ engineering to a distributed video-transcoding backend. Named broadcasters are product context, not direct delivery claims.",
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"allowed_verbs": [
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"developed",
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"engineered",
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"contributed"
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],
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"forbidden": [
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"for CNN, BBC and Al Jazeera",
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"delivered to CNN",
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"customer-embedded"
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],
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"metrics": "unverified"
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},
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{
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"id": "VZ-2",
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"scope": "Developed automated audio/video integration tests and connected quality gates to CI/CD.",
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"allowed_verbs": [
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"developed",
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"automated",
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"integrated"
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],
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"metrics": "unverified"
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},
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{
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"id": "GN-1",
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"scope": "Introduced BDD through a proof of concept and held technical responsibility for test automation, training and Jenkins jobs.",
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"allowed_verbs": [
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"introduced",
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"owned",
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"trained",
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"administered"
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],
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"metrics": "unverified"
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},
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{
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"id": "GN-2",
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"scope": "Developed UIPath RPA proofs of concept and acted as an internal contact.",
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"allowed_verbs": [
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"developed",
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"served"
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],
|
|
"metrics": "unverified"
|
|
},
|
|
{
|
|
"id": "GN-3",
|
|
"scope": "Developed Java/J2EE workflow application features and contributed to integration proofs of concept.",
|
|
"allowed_verbs": [
|
|
"developed",
|
|
"contributed",
|
|
"migrated"
|
|
],
|
|
"metrics": "unverified"
|
|
},
|
|
{
|
|
"id": "BW-1",
|
|
"scope": "Completed officer candidate training and officer school during six years of service in the German Armed Forces (Bundeswehr), leaving service as Second Lieutenant. This establishes military and organisational context only; no technical military role, command scope, deployment, NATO service or clearance is established.",
|
|
"ownership": "Individual service and completed training.",
|
|
"allowed_verbs": [
|
|
"completed",
|
|
"served",
|
|
"left service"
|
|
],
|
|
"forbidden": [
|
|
"current or former security clearance",
|
|
"NATO service",
|
|
"combat role or deployment",
|
|
"technical AI, ICT or cyber work for the military",
|
|
"command responsibility or leadership outcomes not explicitly verified"
|
|
],
|
|
"metrics": "Six years of service and separation as Second Lieutenant are verified; no performance or command-scope metric is established.",
|
|
"source": "User confirmation 2026-07-10; thiessen_linkedin_profile.md",
|
|
"last_verified": "2026-08-27"
|
|
},
|
|
{
|
|
"id": "PP-1",
|
|
"scope": "PERSONAL PROJECT (user-supplied 2026-08-25), not professional work. A self-hosted, single-user investing/signal platform Dennis built for himself: ingests daily US-equity prices, fundamentals and sentiment (LLM-assisted); runs one long-only cross-sectional momentum book (top-quintile residual 12-1 momentum, ATR stop/trail, max 15 concurrent names) through scheduled scan and backtest pipelines; surfaces gated setups in a web dashboard plus Telegram alerts. Legitimate use: evidence of self-directed trading-domain fluency and of an end-to-end ingestion/backtest/alerting build outside work. Full-ownership verbs ARE correct here -- unlike his employer work, this is genuinely solo.",
|
|
"allowed_verbs": [
|
|
"built",
|
|
"developed",
|
|
"designed"
|
|
],
|
|
"forbidden": [
|
|
"any trading track record, PnL, return, Sharpe or backtest performance figure -- none is verified and none may ever be quoted",
|
|
"calling it distributed, scalable, production or multi-user -- it is single-user and self-hosted",
|
|
"implying professional quantitative, trading, finance-domain or investment-management experience",
|
|
"presenting it as employer work or omitting that it is a personal project"
|
|
],
|
|
"metrics": "unverified"
|
|
},
|
|
{
|
|
"id": "PP-2",
|
|
"scope": "Udacity 'AI for Trading' Nanodegree, completed self-study (user-supplied 2026-08-25). Covers quantitative trading fundamentals -- factor construction, alpha signals, backtesting. Pairs with PP-1 as the formal half of self-directed domain grounding.",
|
|
"allowed_verbs": [
|
|
"completed"
|
|
],
|
|
"forbidden": [
|
|
"listing it as an academic degree, professional certification or quant credential",
|
|
"presenting it as equivalent to quantitative research or trading experience",
|
|
"using it to qualify for quant, trader, researcher or portfolio-management roles"
|
|
],
|
|
"metrics": "unverified"
|
|
},
|
|
{
|
|
"id": "PP-3",
|
|
"scope": "PERSONAL PROJECT (user-supplied 2026-08-27), not employer work. A self-hosted Debian server Dennis has operated for ~10 years and administers and hardens himself, running nginx, a mail server, Nextcloud, a VPN server, Docker services and Bitwarden. This is the primary evidence for hands-on Linux administration, system hardening and security configuration, and it is current and continuous - unlike the Bosch Linux work, which ended in 2022. User states he genuinely enjoys this kind of work, including physical infrastructure.",
|
|
"allowed_verbs": [
|
|
"operate",
|
|
"administer",
|
|
"harden",
|
|
"run",
|
|
"maintain",
|
|
"self-host"
|
|
],
|
|
"forbidden": [
|
|
"calling it enterprise, production, multi-user or business-critical infrastructure",
|
|
"implying professional SRE, sysadmin or hosting employment",
|
|
"any uptime, availability, SLA, user-count or scale figure - none is verified",
|
|
"presenting it as employer work or omitting that it is self-hosted and personal",
|
|
"using it as evidence of datacenter or physical-infrastructure experience"
|
|
],
|
|
"metrics": "none; ~10 years of continuous operation is the only quantity, and it is self-reported"
|
|
}
|
|
],
|
|
"skills": [
|
|
{
|
|
"name": "Python",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "SQL",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "PySpark",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "Kafka",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "Airflow",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "AWS",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "CloudFormation",
|
|
"evidence": "production-current",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "Atlassian Compass",
|
|
"evidence": "production-current",
|
|
"output": "allowed",
|
|
"note": "Metadata/catalogue platform for data-product metadata and lineage at Swisscom (user-confirmed 2026-07-29). Practitioner use only — do not claim administration, rollout or ownership. Satisfies 'or similar metadata/catalogue platform' phrasing; is NOT a substitute claim for Purview, Collibra or Alation, which remain unevidenced."
|
|
},
|
|
{
|
|
"name": "Kubernetes",
|
|
"evidence": "production-current-and-historical",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "Ansible",
|
|
"evidence": "production-historical",
|
|
"output": "allowed",
|
|
"note": "User-confirmed 2026-08-27: worked intensively with Ansible at Bosch (2020-2022) for configuration management and infrastructure automation, including the BS-1 ML-inference orchestration. Was absent from claims.json despite already appearing in experience_bosch.md BS-1 bullet variants. Counts as genuine Infrastructure-as-Code evidence alongside CloudFormation. Does NOT by itself license claiming Terraform (still unverified) or GitOps as a named practice (see gitops_pending)."
|
|
},
|
|
{
|
|
"name": "Linux administration",
|
|
"evidence": "production-historical-and-personal-current",
|
|
"output": "allowed",
|
|
"note": "User-confirmed 2026-08-27 and previously ABSENT from claims.json entirely. Professional: at Bosch (2020-2022) Linux servers carried everything - ML platform, Docker hosts, backend services, Ansible control - and he administered and automated them (see BS-6). Personal and current: a self-hosted Debian server he has run and hardened for ~10 years (see PP-3). Hardening and security configuration evidence leans on the personal side; say so rather than implying an employer mandate. Does NOT license claiming datacenter/physical infrastructure work, which remains a genuine gap."
|
|
},
|
|
{
|
|
"name": "Docker",
|
|
"evidence": "production-current-and-historical",
|
|
"output": "allowed"
|
|
},
|
|
{
|
|
"name": "Java",
|
|
"evidence": "production-historical",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "C#",
|
|
"evidence": "production-historical",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "C++",
|
|
"evidence": "production-historical-limited",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "JavaScript",
|
|
"evidence": "production-historical-limited",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "LiteLLM",
|
|
"evidence": "hands-on-current",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "custom GPTs",
|
|
"evidence": "hands-on-current",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "Kiro",
|
|
"evidence": "hands-on-current",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "Copilot",
|
|
"evidence": "hands-on-current",
|
|
"output": "allowed-with-context"
|
|
},
|
|
{
|
|
"name": "quantitative/systematic trading concepts",
|
|
"evidence": "coursework-and-personal-project",
|
|
"output": "allowed-with-context",
|
|
"note": "Udacity AI for Trading nanodegree (PP-2) plus the self-built momentum platform (PP-1): factor construction, cross-sectional/residual momentum, ATR stops, backtesting. Self-directed only — NO professional quant, trading or finance experience. Never list under a Professional Experience skills line without the personal-project context, and never as a quant qualification."
|
|
},
|
|
{
|
|
"name": "backtesting",
|
|
"evidence": "personal-project",
|
|
"output": "allowed-with-context",
|
|
"note": "PP-1 scheduled backtest pipelines, personal scale. Never quote a result or performance figure."
|
|
},
|
|
{
|
|
"name": "TensorFlow/Keras",
|
|
"evidence": "certification",
|
|
"output": "certification-context-only"
|
|
},
|
|
{
|
|
"name": "PyTorch",
|
|
"evidence": "certification",
|
|
"output": "certification-context-only",
|
|
"note": "IBM AI Engineering Professional Certificate (Coursera, 4 Jun 2020) includes the course \"Deep Neural Networks with PyTorch\"; certificate PDF verified 2026-08-27. Same footing as TensorFlow/Keras: certification context only, never presented as production or project experience."
|
|
},
|
|
{
|
|
"name": "TypeScript",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "FastAPI",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "Flask",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "Django",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "LangChain",
|
|
"evidence": "never-used",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "LangGraph",
|
|
"evidence": "never-used",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "LlamaIndex",
|
|
"evidence": "never-used",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "formal model evaluation",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "LLM fine-tuning",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "Azure",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "GCP",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "Terraform",
|
|
"evidence": "unverified",
|
|
"output": "forbidden"
|
|
},
|
|
{
|
|
"name": "GitOps",
|
|
"evidence": "pending-user-clarification",
|
|
"output": "forbidden",
|
|
"note": "RESOLVED 2026-08-27, and the answer is NO. User confirmed: Ansible playbooks lived in Git, but execution was PUSH-based out of Jenkins/GitLab pipelines - there was no pull-based reconciliation agent (Argo CD, Flux). That is version-controlled, CI-driven infrastructure automation, not GitOps. The word stays forbidden in every document. The SUBSTANCE is writable and should be written: 'versionskontrollierte Infrastrukturautomatisierung mit Ansible aus Git, ausgefuehrt ueber Jenkins-/GitLab-Pipelines'. The Kdo Cy JD names 'Pull-GitOps' explicitly, so precision here is an asset, not a loss."
|
|
}
|
|
],
|
|
"global_forbidden_output_patterns": [
|
|
"petabyte scale",
|
|
"petabyte-scale",
|
|
"own the AWS data platform",
|
|
"LangChain-based",
|
|
"customer-embedded delivery",
|
|
"formal model evaluation",
|
|
"3 consecutive years"
|
|
]
|
|
}
|