Asset Management - Equity Data Scientist, Associate
The U.S. Disciplined Core Equity group within J.P. Morgan Asset Management is seeking a Data Scientist to support AI/ML projects that power our quantitative equity investment strategies. Our team manages approximately $100 billion in U.S. equities, combining advanced quantitative research with fundamental insights of portfolio managers. This role is ideal for candidates early in their careers who are passionate about data science, machine learning, and equity markets, and who want hands-on experience building models and pipelines that inform real investment decisions.
Job Responsibilities
- Prepare, clean, and engineer features from structured and unstructured financial data.
- Develop and test regression or machine learning models for return forecasting, alpha signals and risk insights under the guidance of senior researchers.
- Run portfolio backtests and analyze performance ; test new portfolio construction techniques.
- Build NLP/LLM pipelines for text data and extract signals.
- Collaborate with technology partners to help integrate research models into production.
- Create dashboards and reports to communicate model exposures, performance, and risk to portfolio managers and stakeholders.
Required qualifications, capabilities and skills:
- 0+ years of experience in data science or quantitative research.
- Advanced degree (Master’s or PhD)
- Proficiency in Python.
- Hands‑on experience with ML workflows: feature engineering, cross‑validation, hyperparameter tuning, and model evaluation.
- Clear communication skills, both verbal and written, with the ability to present complex ideas to both technical and non-technical audiences.
- Ability to manage multiple projects and deliver results in a fast-paced environment.
Preferred qualifications, capabilities and skills:
- Advanced Degree in data science, computer science, financial engineering, mathematics, statistics, or other quantitative/technical disciplines is preferred.
- Exposure to quantitative equity research, return prediction, or risk modeling is a plus.
- Experience with NLP/LLM methods (text preprocessing, embeddings, transformers) is a plus