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Data Science & Marchine Learning - Senior Associate - Asset Management

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 19 days ago

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Compensation: Not specified
City: London
Country: United Kingdom

Join the J.P. Morgan Asset Management Data Science team to develop and scale AI/ML solutions that support investment decision-making, client engagement, and operational effectiveness. You will work across the full data science lifecycle—from data acquisition and wrangling to model selection, training, and visualization—and partner with portfolio managers, engineers, and UX to build tools that deliver real-time insights. The role involves working in a globally distributed team on greenfield analytics projects and requires strong delivery, communication, and technical skills.

Location: LONDON, United Kingdom

The J.P. Morgan Asset Management Data Science Team (JPMAM) is part of J.P. Morgan Asset & Wealth

Management. The JPMAM Data Science team focuses primarily on developing novel AI/ML methods to drive innovative solutions for amplifying data-driven investment decision-making, improved client engagement, and operational effectiveness.

Job Summary

As a Data Scientist Senior Associate in the J.P. Morgan Asset Management Data Science Team (JPMAM), you will work closely with investment and data science professionals across Asset Management to proactively source, due diligence and draw insights from in-house investment and alternative data.

This is an exciting opportunity to join a small, dynamic team with the resources and impact of one of the world’s largest companies. We are looking for problem-solvers with a passion for building greenfield analytic solutions and helping to scale them for greater impact. The successful candidate will be expected to work on projects along the full data science spectrum. From data acquisition and wrangling, to model selection to presentation and data visualization. The role requires the successful candidate to work as a part of a globally distributed data science team. They will work with stakeholders and subject matter experts to understand problems then find innovative, practical solutions. The successful candidate will be able to evidence a history of delivery and innovation.

Job Responsibilities

Building tools and systems to understand decision data, context and events around it to enhance JPMAM’s decision attribution capabilities and systematically identify opportunities
Working with portfolio managers to understand sources of alpha and opportunities to improve decision-making process
Working with partners in technology and user experience to build out tools providing real-time insights to portfolio managers and their teams
Given the subject matter, a non-financial background would be acceptable if the candidate had an exceptionally strong data science skillset

Required qualifications, capabilities and skills

Masters Degree or PhD, in computer science, statistics, or other quantitative field
Strong analytical/modelling skills and business orientation with proven ability to use data and analytics to drive business results; strong technical background
Demonstrated experience working within a data science team
- Timeseries analysis and modelling
- Training and fine-tuning of the ML model for investment models
- Strong knowledge of Python for data scientists (e.g., pandas), traditional ML and deep learning libraries (e.g., scikit learn, xgboost, TensorFlow, Torch, etc.)
- Data manipulation languages (e.g., SQL)
- Data visualization / presentation skills (e.g., Tableau)
Demonstrated experience working with engineering, developers and other technology teams
- Writing production quality code, unit testing and familiarity with version control
- Familiarity with cloud-based technologies
Demonstrated experience using alternative datasets in investing and alpha research
- In-depth understanding of financial markets required
Strong communications skills and the ability to present findings to a non-technical audience
Passion for learning and adopting a wide range of techniques in an agile environment

Preferred qualifications, capabilities, and skills

Prior experience working in alpha capture, performance attribution or trading / decision analytics role
Front office experience in finance (preferably buyside)
Familiarity in incorporating unstructured data into investment research
Knowledge of alternative data landscape
CFA

Develop, test, and maintain critical data pipelines and architectures across multiple technical areas

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