Rust still going. Added Databricks training to the mix. CQF Module 2 is deep into risk. VaR, GARCH, stylized facts. The stack keeps growing. Late nights after the kids are down, same as always.
> cogitator.about
I work in risk.
Started in credit methodology for private banking. Moved into market risk and quantitative analytics. Then investment risk for asset management. Eventually stopped separating models from systems.
The unquantified risk was never in the portfolios. It's around them.
CQF in progress. ARPM incoming. Off the clock, split keyboards, terminal configs, and hardware that demand constant appeasement.
> log.latest
Last ski days of the season. The mountains are done, no more snow. Kids loved it. Made every run count.
I produce nothing. Figures, models, scripts to tie it all together, but nothing you can hold. I love the work though. Still sitting with that one.
Module 1 exam done. Back in the gym after a break. Already signed up for ARPM after CQF wraps up. Rainy weekend with the kids, the best kind.
> cogitator.skills
Measured it, monitored it, built the frameworks around it. Daily identification, escalation, and reporting across funds, insurance portfolios, and mandates. Most of the work is making sure nothing is invisible. The tail risk is always in the process, not the portfolio.
Pricing, decomposition, simulation, stress testing, backtesting. Time series modeling, attribution, numerical methods. VaR is the output. The interesting part is what goes into it. Everything is normally distributed until it isn't.
Several, across different paradigms. The right one depends on the problem. The wrong one teaches you something anyway. Neovim doesn't configure itself though.
Web frameworks for dashboards and APIs. Orchestration tools for pipelines. Visualization libraries for the charts nobody reads until something breaks. The frameworks change every few years. The problems they solve don't. The litany of deployment stays the same.
Relational databases at the core. Analytical query engines and columnar storage for the heavy lifting. Object storage when files need a home. ETL pipelines connecting everything that wasn't designed to talk to each other. Most of data engineering is convincing systems to cooperate.
Portfolio management systems, risk analytics engines, ESG data providers. The vendor ecosystem that every risk function depends on and nobody fully trusts. The real skill is knowing what each one actually does well and building around the rest.
Containers, orchestration, CI/CD, cloud, monitoring. The infrastructure that keeps the machine spirits running. Deployment is a ritual. Observability is a prayer.
> cogitator.experience
Senior Risk Manager, Deputy CRO
Baloise Asset Management · Basel
Risk Management
- ▹ Initiated and led creation of unified risk infrastructure and comprehensive investment risk framework for traditional assets across funds, insurance funds, and mandates
- ▹ Developed production-grade risk analytics platform (BAM ONE) transforming manual processes into automated dashboards, integrating data vendors
- ▹ Implemented KPIs covering risk analytics (market, liquidity, credit, counterparty, and ESG risk)
- ▹ Performed daily identification, analysis, and escalation of risk issues across all risk factors
- ▹ Led investment risk dialogues with portfolio managers and established automated reporting workflows to senior management and regulatory authorities
- ▹ Managed and mentored two junior risk analysts, coordinating work assignments, providing technical guidance, and ensuring quality of risk analysis deliverables
- ▹ Introduced modern technology stack across business units with full DevOps ownership
- ▹ Served as Deputy Chief Risk Officer ensuring risk infrastructure alignment with strategic objectives
Investment Risk Specialist
UBS Fund Management AG · Basel
ManCo Products
- ▹ Steered investment risk framework under regulatory requirements for UBS and White Labelling funds
- ▹ Led software development of proprietary risk analytics and reporting solutions (web applications and tools)
- ▹ Investigated VaR figures and large overnight changes, conducted stress testing and backtesting, evaluated economic exposures
- ▹ Monitored fund's asset/liability liquidity risk and credit risks in securities lending and OTC transactions
- ▹ Performed pre-launch fund risk assessments and escalated exceptions to portfolio managers and relevant governing bodies
- ▹ Produced periodic investment risk reports for Executive Committee and Board of Directors
- ▹ Deputized Investment Risk team lead and served as single point of contact for robotics and data science projects
Performance Analyst
Bank Julius Baer · Zürich
Performance Controlling & Risk Analytics
- ▹ Ensured GIPS compliance and handled performance measurement topics from all Bank areas and locations
- ▹ Monitored and reviewed performance development of client accounts and identified performance outliers
- ▹ Performed attribution analysis of equity/fixed income/multi-asset portfolios using factor-based risk models and total return attribution
- ▹ Analyzed performance differences along the investment process through contribution and attribution analysis
- ▹ Enhanced IT solutions for performance measurement and complex risk-return analysis across the Bank
Quantitative Analyst
Bank Julius Baer · Zürich
Risk Analytics
- ▹ Fundamental Review of the Trading Book (FRTB) implementation - analyzed capital impact and evaluated vendor solutions for exotic derivatives
- ▹ Led weekly investment controlling for actively managed certificates (AMC), including trader interaction and trade approvals
- ▹ Participated in value at risk production and daily data checks
- ▹ Additionally supported IRRBB initiative with deposit volume forecasting model
Risk Supervisor
Société Générale Private Banking · Monaco
Credit Methodology Lombard
- ▹ Designed credit risk framework for securities-backed lending in private banking
- ▹ Evaluated lending values and margin requirements across equity, fixed income, and structured products
- ▹ Built monitoring tools automating daily risk reports for front office and regulators
- ▹ Developed custom controls for collateral coverage and concentration risks
> cogitator.projects
BAM ONE
Enterprise Risk Analytics Platform
Baloise Asset Management
Initiated and led development from concept to production, creating unified risk infrastructure that transformed manual processes into central analytics hub
Built cloud-native ecosystem: Python/Dash, Mage AI orchestration, MinIO data lake, PostgreSQL, Trino with Iceberg tables, integrated with SimCorp/Bloomberg/MSCI; full DevOps ownership (OpenShift, Jenkins/ArgoCD, Prometheus/Grafana)
> impact: FINMA praised as exemplary implementation; enabled shift from monthly to daily risk monitoring across all risk dimensions
Python Dash FastAPI Mage AI MinIO PostgreSQL Trino Iceberg OpenShift Jenkins ArgoCD
Risk Cockpit
Investment Risk Monitoring Platform
UBS Fund Management
Led development as sole technical owner and lead software developer, modernizing from local R Shiny instances to centralized web application
Built complete data ecosystem: automated pipelines from multiple sources, SQLite backend, threshold monitoring with alerting; extended with Python while maintaining R core
> impact: Standardized risk reporting across team, supporting regulatory requirements for UBS and White Labelling funds
R Shiny Python SQLite
Structured Products Risk Approximation Model
ML-based Regulatory Risk Scoring
Bank Julius Baer
Co-developed ML prototype with external vendor for regulatory risk scoring of third-party structured products lacking pricing models
Implemented k-nearest neighbor algorithm using term sheet characteristics (underlying, maturity, barriers) with automated parsing and vendor API integration
> impact: Enabled regulatory compliance for previously unmeasurable products; prototype became foundation for production system
Python ML/KNN API Integration
FRTB Capital Charge Vendor Evaluation
Exotic Derivatives Analysis
Bank Julius Baer
Led technical evaluation of MSCI RiskMetrics module for exotic derivatives capital charges under FRTB framework
Decomposed complex products using vendor's scripting language into component risks (FX, options, bonds); validated Monte Carlo valuations against front office models
> impact: Delivered buy/no-buy recommendation based on model accuracy, product coverage, and implementation complexity
MSCI RiskMetrics Monte Carlo Derivatives
Deposit Volume Forecasting Model (IRRBB)
Time Series Forecasting
Bank Julius Baer
Implemented academic research for Banking Book Risk team to forecast deposit volumes under rate scenarios using R time series models (ARIMA/VAR)
> impact: Model adopted for internal reporting
R ARIMA VAR Time Series
> cogitator.education
Master of Science in Finance (MSc)
2016 - 2017Research Track Quantitative Finance
Université Paris-Dauphine, PSL Research University · Paris
Thesis: Agricultural Derivative Markets Integration: A Graph Theory Analysis
Bachelor of Business Administration (BBA)
2009 - 2013Banking and Financial Markets
EDHEC Business School · Nice
Thesis: Credit Risk Calculation and Management