Senior Data Scientist – Stress Testing

Location: London / India

Experience Level: 7+ years

Role Overview:

We are looking for a highly skilled Senior Data Scientist to lead the development of advanced analytical models for stress testing in a brokerage environment. The candidate will be responsible for designing predictive models, stress-testing frameworks, and risk analytics solutions to support regulatory and internal risk assessments.

Key Responsibilities:
• Develop and implement machine learning and statistical models for stress testing, scenario analysis, and risk forecasting.
• Work with large-scale financial datasets, including transactional, market, and liquidity data, to extract meaningful insights.
• Design stress-testing methodologies to assess liquidity under various stress conditions (market shocks, funding liquidity risk, counterparty risks, etc.).
• Collaborate with quantitative analysts, risk managers, and financial engineers to refine stress scenarios and optimise risk mitigation strategies.
• Build automated pipelines for model deployment and monitoring using Python, Snowflake, and cloud-based platforms (AWS/Azure/GCP).
• Present findings and insights to senior stakeholders, including risk committees and regulatory bodies.

Key Skills & Requirements:
• Strong expertise in quantitative finance, statistical modelling, and time series analysis.
• Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL.
• Experience with stress testing frameworks, Monte Carlo simulations, and liquidity risk models.
• Familiarity with financial regulations (Basel III, IFRS 9, liquidity coverage ratio (LCR), net stable funding ratio (NSFR)).
• Knowledge of data engineering workflows and experience working with cloud-based data platforms (Snowflake, AWS Redshift, BigQuery).
• Strong communication skills and ability to work cross-functionally with financial, risk, and IT teams.