JPMorgan Investment Risk & Analytics - Quant Modeling Associate 

India, Maharashtra, Mumbai 

846984989

Job responsibilities:

• Design, develop, and deploy advanced AI/ML models to derive actionable insights, automate processes, and facilitate strategic decision-making across various business units.
• Collaborate with teams to design and oversee the end-to-end lifecycle of AI/ML initiatives – from problem scoping, data engineering, model development, validation, deployment, to monitoring.
• Lead the model development process, including tasks such as data wrangling/analysis, model training, testing, and selection.
• Conduct risk modeling, scenario analysis, and business impact evaluations to ensure AI/ML solutions are robust, ethical, and aligned with organizational goals.
• Drive experimentation with advanced techniques such as deep learning, generative AI (e.g., LLMs, GANs), and reinforcement learning to solve complex business challenges and create value.
• Collaborate with Technology on model testing, implementation, and production.
• Deliver written, visual, and oral presentation of modeling results to business and technical stakeholders.
• Stay abreast of emerging trends and research in AI and machine learning, and assess their potential application within the organization.
• Represent risk analytics in governance forums, risk committees, and audit discussions.
• Participate in regulatory and validation exams by providing documentation and responses to regulators and internal validators.
• Partner with non-credit risk groups to identify and understand the simultaneous impact of multiple risks, such as product, fiduciary, counterparty, concentration, ESG/climate, liquidity, and their effect on investments.

Required qualifications, capabilities, and skills

• 3+ years of hands-on experience in data science, machine learning, or AI.
• Bachelors/Master/PhD degree in Computer Science / Data Science / Mathematics / Statistics / relevant STEM field is highly preferred.
• Demonstrated experience with generative AI technologies such as transformers, large language models, or diffusion models.
• Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning (e.g., ensemble methods, NLP, time-series), Probability Theory and Linear Algebra.
• Have experience with investment products including fixed income, equity, and mutual funds.
• Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, LangChain, LangGraph etc.).
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Logical thought process, ability to scope out an open-ended problem into data driven solution.
• Strong quantitative and analytical skills and ability to work with diverse cultures in a global team.