You are someone who thrives in a high-performance environment, bringing a growth mindset and entrepreneurial spirit to tackle meaningful challenges that have a real impact.
In return for your drive, determination, and curiosity, we’ll provide the resources, mentorship, and opportunities to help you quickly broaden your expertise, grow into a well-rounded professional, and contribute to work that truly makes a difference.
As a Principal Data Scientist, you will lead the design, delivery, and governance of GenAI- and ML-powered risk solutions that mitigate risks, sharpen controls, and make the risk function markedly more efficient.
You will own the end-to-end delivery of GenAI in risk from concept to production, and architect and build retrieval-augmented generation (RAG) pipelines and evaluators (prompt design, grounding data curation, guardrails, red-teaming, offline/online evals), ensuring factuality, privacy, and cost/performance balance.
You will develop and ship models and services hands-on in Python (data prep, feature engineering, training/inference, APIs); write high-quality, tested code and drive code reviews in GitHub, query and transform data with SQL; partner closely with data engineering to model lineage and build reliable pipelines using dbt on Snowflake (or similar modern data stack).
You will apply traditional ML where appropriate (classification, anomaly detection, NLP, forecasting) and integrate with GenAI approaches; choose the simplest method that meets risk and performance requirements.
Additionally, you will produce using MLOps/LLMOps best practices: CI/CD, containers, orchestration, feature/embedding stores, vector search, monitoring (data drift, model decay, hallucination/factuality) and embed robust risk & model governance: documentation, explainability, validation/testing standards.
You will lead cross-functional partnerships with Risk/Compliance, Legal, Security, Product, and Engineering; translate risk policy into technical requirements and communicate trade-offs to senior stakeholders.
You will mentor and upskill data scientists/analysts; establish reusable components, templates, and internal best practices for GenAI in risk.
Your work will materially improve how risk is identified, assessed, and mitigated—shortening investigation cycles, reducing false positives, automating manual controls, and strengthening regulatory compliance while enabling the business to move faster with confidence.
You will be based in Europe as part of our Risk Technology & AI team. This team partners with risk and business leaders to modernize controls, streamline operations, and unlock value from data and AI across the enterprise.
:quality(80))
:quality(80))
:quality(80))