J.P. Morgan is looking to accelerate the firm’s data and analytics journey, ensuring the quality, integrity, and security of the company's data, and leveraging this data to generate insights and drive decision-making.
Requirements
- PhD in a quantitative discipline, e.g. Econometrics, Finance/Accounting, Mathematics, Computer Science, Operations Research
- Hands-on experience and solid understanding of machine learning and deep learning methods
- Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Experience with big data and scalable model training
- Ability to develop and debug production-quality code
- Solid experience in writing unit tests, integration tests, and regression tests
Responsibilities
- Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
- Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as time-series analysis and modelling, constrained optimization and prediction for large systems, prescriptive analytics, and decision-making in dynamical systems
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
- Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
Other
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Ability to conduct literature research in unfamiliar fields
- Ability to work both independently and in highly collaborative team environments
- PhD in a quantitative discipline
