Investment Risk & Analytics - Quant Modeling Senior Associate
JPMorgan ChaseBring your Expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.
As a part of the Investment Risk & Analytics team, you are at the center of keeping JPMorgan Chase strong and resilient. Managed Strategies included JPMorgan’s own proprietary products and third-party funds to include registered funds, exchange traded notes (ETNs), exchange traded funds (ETFs), separately managed accounts, hedge funds, and private equity and real estate funds, etc.
We are looking for individuals who can partner with senior members of our team to oversee business activities, models and methodologies related to investment risk. with an emphasis on developing new tools and methodologies that will aid in risk quantification.
Job responsibilities
- Design, develop, and deploy advanced AI/ML models to drive insights, automate processes, and support strategic decisions.
- Lead and collaborate on the end-to-end lifecycle of AI/ML initiatives, including data engineering, model development, validation, deployment, and monitoring.
- Conduct risk modeling, scenario analysis, and business impact evaluations to ensure robust, ethical, and goal-aligned solutions.
- Experiment with advanced techniques like deep learning, generative AI, and reinforcement learning to solve business challenges.
- Apply advanced statistics, econometrics, and mathematical skills for modeling and analysis.
- Work with Technology teams on model testing, implementation, and production.
- Mentor junior data scientists and foster a collaborative culture.
- Present modeling results to business and technical stakeholders in written, visual, and oral formats.
- Stay updated on AI and machine learning trends and assess their organizational impact.
- Contribute to process innovation and team strategy within the asset-class group.
- Represent risk analytics in governance forums, risk committees, and audits, and partner with risk groups to address multiple risk impacts.
Required qualifications, capabilities, and skills
5+ years of hands-on experience in data science, machine learning, or AI.
Bachelors/Master/PhD degree in Computer Science / Data Science / Mathematics / Statistics
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.
Experience with Machine Learning & Deep Learning concepts including data representations, neural network architectures, custom loss functions.
Foundational mathematical concepts, including continuity, differentiability, Taylor formulas, differential equations, integration, measure theory, linear algebra, discrete and continuous probabilities, Markov chains, regression.
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 a global team.
Preferred qualifications, capabilities, and skills
Relevant STEM field is highly preferred.