Files
claude-resume-kit/resume_builder/canonical/claims.json
T
dennisthiessenandClaude Opus 5 b97dec978a feat(kb): add trading-domain evidence as PP-1 and PP-2
claims.json had zero hits for trading, finance or quant, so a real
capability could not legally reach any document: the file is the
highest-authority source and nothing outside it is claimable. Surfaced
while assessing the Citadel Securities Platform Engineer req (Zurich),
where domain fluency is exactly what was missing.

PP-1 is the self-built investing/signal platform: US-equity price,
fundamental and LLM-assisted sentiment ingestion, a long-only
cross-sectional residual 12-1 momentum book with ATR stop/trail and max
15 concurrent names, scheduled scan and backtest pipelines, web
dashboard and Telegram alerts. PP-2 is the Udacity AI for Trading
nanodegree. Two allowed-with-context skills reference both.

Written defensively, because this is the kind of entry a later run
inflates. Each carries an explicit forbidden list: no PnL, Sharpe,
return or backtest figure may EVER be quoted (none is verified); PP-1 is
single-user and self-hosted, so never distributed, scalable, production
or multi-user; neither implies professional quantitative, trading or
finance experience; the nanodegree is never an academic or quant
credential. Legitimate use is self-directed domain fluency plus an
end-to-end ingestion/backtest/alerting build outside work.

PP-1 is also the one claim where full-ownership verbs are correct - it
is genuinely solo, unlike the employer work that Scope Discipline
governs. Stated in the scope so the two rules do not collide later.

JSON valid, validator PASS, 9/9 tests pass.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MHtzyTKBcg6BWhD5qFegtK
2026-08-25 23:18:18 +02:00

312 lines
18 KiB
JSON

{
"schema_version": 1,
"last_verified": "2026-07-27",
"authority": {
"description": "Machine-readable source of truth for all future application documents.",
"precedence": ["canonical claims", "config corrections", "verified references", "experience files", "bundles"],
"raw_extractions_are_immutable": true,
"historical_outputs_are_never_sources": true
},
"identity": {
"name": "Dennis Thiessen",
"degree_suffix": "M.Eng.",
"email": "dennis@thiessen.io",
"phone": "+41 795 955 585",
"location": "Bern, Switzerland",
"linkedin": "linkedin.com/in/dennis-thiessen",
"citizenship": "German citizen (EU)",
"swiss_permit": "B residence permit",
"swiss_work_authorization": "Authorized to work in Switzerland; no visa or employer sponsorship required",
"work_authorization_source": "User-confirmed 2026-07-27",
"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",
"languages": {"German": "native", "English": "fluent", "Norwegian": "basic", "Russian": "basic"},
"forbidden_personal_data": ["date of birth", "marital status", "gender", "children"]
},
"education": [
{
"id": "EDU-MENG",
"degree": "M.Eng. Computer Aided Engineering",
"display_focus": "Software Design & Engineering",
"institution": "Universitat der Bundeswehr Munchen",
"start": "2012-04",
"end": "2013-10",
"thesis_institution": "Tongji University, Shanghai",
"thesis_title": "Development of a Web-Based Remote Fault Diagnosis System",
"thesis_grade": "1.0",
"thesis_relative_grade": "ECTS B (top 35%); official certificate on file",
"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.",
"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.",
"transcripts_language": "English-language originals available for B.Eng. and M.Eng."
},
{
"id": "EDU-BENG",
"degree": "B.Eng. Information and Telecommunication Technologies",
"institution": "Universitat der Bundeswehr Munchen",
"start": "2009-10",
"end": "2012-10"
}
],
"employment": [
{
"id": "SWISSCOM",
"employer": "Swisscom (Schweiz) AG",
"location": "Bern, Switzerland",
"display_title": "Staff Data, Analytics & AI Engineer",
"start": "2023-10",
"end": "present",
"title_history": [
{"title": "Senior Data, Analytics & AI Engineer", "start": "2023-10", "end": "2025-04"},
{"title": "Staff Data, Analytics & AI Engineer", "start": "2025-04", "end": "present"}
]
},
{
"id": "BOSCH",
"employer": "Robert Bosch Semiconductor Manufacturing Dresden GmbH",
"location": "Dresden, Germany",
"official_title": "Engineer / Senior Engineer, Data Analysis",
"display_title": "Senior Engineer, Data Analysis (Data & ML Engineering)",
"start": "2020-02",
"end": "2022-12"
},
{
"id": "FRAUNHOFER",
"employer": "Fraunhofer-Center for Maritime Logistics and Services CML",
"location": "Hamburg, Germany",
"official_title": "Wissenschaftlicher Mitarbeiter",
"display_title": "Research Software Engineer",
"start": "2018-09",
"end": "2019-10"
},
{
"id": "VIZRT",
"employer": "Vizrt",
"location": "Bergen, Norway",
"official_title": "Test Automation Engineer",
"display_title": "Test Automation / DevOps Engineer",
"start": "2017-07",
"end": "2018-05"
},
{
"id": "GENERALI",
"employer": "Generali Deutschland Informatik Services GmbH",
"location": "Hamburg, Germany",
"display_title": "IT Consultant",
"start": "2015-05",
"end": "2017-06"
},
{
"id": "CAPGEMINI",
"employer": "Capgemini Deutschland GmbH",
"location": "Hamburg, Germany",
"display_title": "Software Engineer",
"start": "2014-11",
"end": "2015-05"
}
],
"claims": [
{
"id": "SW-1",
"scope": "Primary engineer for pipelines in owned Fulfillment and Product Analysis domains; contributor to the wider company migration.",
"allowed_verbs": ["migrated", "implemented", "contributed"],
"forbidden": ["led the migration of the legacy warehouse", "sole technical lead", "migrated the company warehouse", "owned the full migration"],
"metrics": "unverified"
},
{
"id": "SW-2",
"scope": "Component Owner for business-critical Fulfillment ETL pipelines, including operation, data quality, governance, incidents and on-call obligations.",
"allowed_verbs": ["own", "operate", "maintain", "serve"],
"metrics": "unverified"
},
{
"id": "SW-3",
"scope": "Build and operate Python data applications on Kubernetes with GitLab CI/CD within the team environment.",
"allowed_verbs": ["build", "deploy", "operate"],
"metrics": "unverified"
},
{
"id": "SW-4",
"scope": "Deliver data products, dashboards and analyses with internal B2B stakeholders and product owners; not external consulting or strategic-account delivery.",
"allowed_verbs": ["deliver", "translate", "partner", "support"],
"forbidden": ["customer-embedded delivery", "strategic customer delivery", "C-suite advisor"],
"metrics": "unverified"
},
{
"id": "SW-5",
"scope": "Mandatory rotating team Security Champion role for 2025/2026 only; not an award, certification or multi-year distinction.",
"allowed_verbs": ["serve"],
"forbidden": ["3 consecutive years", "2023-2026", "Security Champion x3", "owning DevSecOps compliance"],
"metrics": "100 hours of training and an assessment are source-backed; use only when relevant"
},
{
"id": "SW-6",
"scope": "Hands-on PySpark use at Swisscom; scale and performance metrics are not verified.",
"allowed_verbs": ["use", "develop", "process"],
"metrics": "unverified"
},
{
"id": "SW-7",
"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.",
"allowed_verbs": ["build", "model", "onboard", "contribute", "document", "maintain"],
"forbidden": ["built a Data Mesh", "built the Data Mesh", "built AWS Data Mesh", "own the AWS data platform", "own the data platform", "own Atlassian Compass", "administered Compass", "rolled out Compass"],
"metrics": "unverified"
},
{
"id": "SW-8",
"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.",
"allowed_verbs": ["configured", "used", "integrated"],
"forbidden": ["built production LLM systems", "deployed LLM systems", "built LangChain", "agent orchestration", "formal LLM evaluation", "fine-tuned models"],
"metrics": "unverified"
},
{
"id": "BS-1",
"scope": "Designed and executed integration of containerized ML inference into a 24/7 semiconductor production environment; model-development ownership is not established.",
"allowed_verbs": ["integrated", "containerized", "deployed", "orchestrated"],
"forbidden": ["trained the image classification model", "owned the full ML lifecycle"],
"metrics": "qualitative reduction in manual classification is source-backed; exact amount unverified"
},
{
"id": "BS-2",
"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.",
"allowed_verbs": ["developed", "built"],
"metrics": "unverified"
},
{
"id": "BS-3",
"scope": "Confirmed Application Owner responsibilities for analytics applications and upstream pipelines, including SLOs, vendors, training and documentation.",
"allowed_verbs": ["served", "owned", "managed", "defined"],
"metrics": "unverified"
},
{
"id": "BS-4",
"scope": "Built an ELK/Kafka anomaly-detection proof of concept and monitoring; not a company-wide observability platform.",
"allowed_verbs": ["built", "implemented", "validated"],
"forbidden": ["built the observability platform", "enterprise observability platform"],
"metrics": "unverified"
},
{
"id": "BS-5",
"scope": "Co-owned the TIBCO Spotfire environment, built C# extensions and co-presented at TIBCO Analytics Forum 2022.",
"allowed_verbs": ["co-owned", "built", "co-presented"],
"metrics": "unverified"
},
{
"id": "FC-1",
"scope": "Set up Jenkins CI/CD and contributed to SCEDAS development and maintenance.",
"allowed_verbs": ["set up", "developed", "maintained"],
"metrics": "unverified"
},
{
"id": "FC-2",
"scope": "Contributed ML/NLP components to ARTUS; no publication or model-training ownership.",
"allowed_verbs": ["contributed", "implemented", "supported"],
"forbidden": ["led ARTUS", "trained the speech model"],
"metrics": "unverified"
},
{
"id": "FC-3",
"scope": "Developed containerized microservices for the MISSION research platform.",
"allowed_verbs": ["developed", "built"],
"metrics": "unverified"
},
{
"id": "VZ-1",
"scope": "Contributed Python and C++ engineering to a distributed video-transcoding backend. Named broadcasters are product context, not direct delivery claims.",
"allowed_verbs": ["developed", "engineered", "contributed"],
"forbidden": ["for CNN, BBC and Al Jazeera", "delivered to CNN", "customer-embedded"],
"metrics": "unverified"
},
{
"id": "VZ-2",
"scope": "Developed automated audio/video integration tests and connected quality gates to CI/CD.",
"allowed_verbs": ["developed", "automated", "integrated"],
"metrics": "unverified"
},
{
"id": "GN-1",
"scope": "Introduced BDD through a proof of concept and held technical responsibility for test automation, training and Jenkins jobs.",
"allowed_verbs": ["introduced", "owned", "trained", "administered"],
"metrics": "unverified"
},
{
"id": "GN-2",
"scope": "Developed UIPath RPA proofs of concept and acted as an internal contact.",
"allowed_verbs": ["developed", "served"],
"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": "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"
}
],
"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": "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": "coursework-or-personal-unverified", "output": "certification-context-only"},
{"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"}
],
"global_forbidden_output_patterns": [
"petabyte scale",
"petabyte-scale",
"own the AWS data platform",
"LangChain-based",
"customer-embedded delivery",
"formal model evaluation",
"3 consecutive years"
]
}