JPMorgan Data Scientist Associate Asset Wealth Management Risk 

India, Karnataka, Bengaluru 

294894706

Job responsibilities :

• Work with peers and stakeholders to identify use cases and opportunities for Data Science to create value. Use your knowledge of Computer Science, Statistics, Mathematics and Data Science techniques to provide further insights into security and portfolio risk analytics.

• Lead continuous improvements in our adopted AI/ML and statistical technics used in our data and analytics validation process.

• Collaborate, design, and deliver solutions that are flexible and scalable using the firm’s approved new technologies and tools, such as AI and LLMs. Use citizen developer journey platform to find efficiencies in our processes.

• Contribute to the analysis of new and large data sets and assist with their onboarding, following our best practice data model and architecture using big data platforms.

• Contribute to the research and enhancement of the risk methodology for AWM Risk Analytics. The methodology covers sensitivity, stress, VaR, factor modeling, and Lending Value pricing for investment (market), counterparty (credit), and liquidity risk.

Required qualifications, capabilities, and skills

• 2+ years experience as a Data Scientist or in an adjacent quantitative role.

• A quantitative, technically proficient individual who is detail-oriented, able to multi-task, and work independently.

• Excellent communication skills.

• A strong understanding of statistics, applied AI/ML techniques, and a practical problem-solving mindset.

• Knowledge in modular programming in SQL, Python, ML, AWS Sagemaker, TensorFlow or alike.

Preferred qualifications, capabilities, and skills :

• Practical experience in financial markets in a quantitative analysis/research role within Risk Management, a Front Office role, or equivalent is a plus.

• Knowledge of asset pricing, VaR backtesting techniques, and model performance testing is a plus.

• A degree in a quantitative or technology field (Economics, Maths/Statistics, Engineering, Computer Science or equivalent) is preferred.