_sdn._bhd..jpg){kind=small}
Risk Reporting Senior Officer
Hybrid · Warsaw, Mazovia, Poland
Job Summary
Lead and execute content generation and quantitative analysis on market risk, leveraging extensive industry experience to modernize the core Market Risk platform; collaborate with technology, business, and control functions to translate complex risk requirements into practical solutions; apply advanced data science, machine learning, and AI techniques to develop prediction capabilities and analytical insights into markets portfolios; design, develop, and maintain data models and schemas to support risk data aggregation, analysis, and reporting; leverage cloud platforms for scalable risk analytics; serve as Product Owner for risk management initiatives, defining roadmaps and ensuring alignment with regulatory requirements; monitor data governance and data quality KPIs and drive automation to reduce manual processes; effectively communicate complex quantitative concepts and risk insights to diverse audiences including junior analysts and senior management; require deep knowledge of traded products, Basel 2.5/FRTB, Python, ML, cloud data tools, and governance frameworks.
Required Qualifications
- Essential 10+ years in Market Risk, Risk Reporting or related financial risk discipline
- Deep knowledge of traded products across equities, rates, credit, FX and commodities, and associated price risk concepts—sensitivities, VaR, stress testing, P&L attribution
- Solid working knowledge of Basel 2.5 and FRTB, and supervisory expectations of major European and/or American regulators
- Proficiency in Python; ability to design and implement relational data models and physical table structures
- Working knowledge of major cloud platforms (AWS, Azure, GCP) and core data services—data lakes, managed warehouses, serverless compute and orchestration
- Foundational knowledge of ML techniques—supervised/unsupervised learning, time series, anomaly detection—and their application in a risk context
- Awareness of the GenAI landscape including LLMs, prompt engineering and RAG, and emerging use cases in financial services
- Degree-educated in a technology, quantitative, finance or related discipline
- Hands-on ML/AI experience applied to financial risk data—outlier detection, P&L pattern recognition, NLP-driven commentary generation
- Experience with LLM APIs (Gemini, Anthropic) or orchestration frameworks (LangChain, LlamaIndex)
- Knowledge of model risk governance in a banking context
- Project management experience—Agile, Waterfall or hybrid
- Experience delivering target operating model or large-scale technology or reporting transformation programs
- Conscientious, dedicated and focused with a strong drive to deliver
- Composed under pressure with the ability to prioritize across competing demands
- Thoughtful early adopter of emerging technology with rigorous risk management
Apply with one swipe on Sorce. We auto-fill applications and apply on your behalf — no cover letters, no 40-minute forms.
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.