Description
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 workflowsand experience working with cloud-based data platforms(Snowflake,AWS Redshift ,BigQuery).
- Strong communication skillsand abilityto work cross-functionallywithfinancial,risk,and IT teams.