Data Science Developer - VP

Last updated 3 hours ago
Job Type:Full Time

About J.P. Morgan Corporate & Investment Bank

J.P. Morgan Chase is a global leader across banking, markets and investor services. The world’s most important corporations, governments and institutions entrust us with their business in more than 100 countries. With $18 trillion of assets under custody and $393 billion in deposits, the Corporate & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. The firm is a leader in investment banking, financial services for consumers, small business and commercial banking, financial transaction processing, asset management, and private equity. The Chief Data Office has a mandate set and actively supported at the board level to transform data management towards demonstrable shareholder value. The FDM Discovery Analytics team, have a firm wide remit to deliver a broad set of data capabilities including the functional and technical vision for data discovery and partnering with business line to improve the commercial offering of data through the adoption ML and AI techniques.

Department Description

The FDM group is accountable for transforming approach and policies for managing data to create an industry-leading data environment in terms of control, cost, and efficiency. The program scope continues to evolve and encompasses cultural, behavioral, procedural and systemic transformation across the full range of data domains.

Role Background

The group is accountable for data discovery using machine learning with an industry-leading data environment covering both modern and heritage data estates. Artificial intelligence (AI) is reshaping how we work, interact and share information and content. AI and Machine Learning (ML) technologies are being incorporated into our data activities. These are helping to influence and re-shape our risk assessment processes, dataflow analysis, portfolio and catalog quality scoring, the identification of regulatory data, and operational and application-level interactions.

Key roles and responsibilities:

  • The successful candidates will join a team focused on supporting the data strategy and execution of the for data prediction. Principal to this will analyzing and understanding the data through traditional statistics and Machine Learning techniques.
  • Design and build predictive models that substantially increase the value that we provide to our customers and the efficiency of our operations.
  • The candidate will help forge the framework for machine learning for data discovery; this includes building algorithms and productionizing the use of them across a parallel processed environment include cloud based solutions.


  • Development new ML models and enhance existing ones
  • Bring additional expertise to the team, through modern design
  • Build scalable algorithms
  • Produce data visualizations that effectively communicate information related to where data discovery is needed for business case objectives.

Experience Required

  • Experience of data analysis and data processing using Python to write Machine Learning methods to analyze large and complex datasets
  • Should have solid Theoretical or practical experience of using supervised Machine Learning: regressions, classifications; Unsupervised Machine Learning: clustering, factor analyses as well as methods of Deep and Reinforcement Learning.


  • Good Mathematical and Algorithms Knowledge and Well-Versed With Probability and Statistics
  • Efficiency In Distributed Computing, Good Command of Unix Tools


  • Graduate degree (MS, or Ph.D.) in Computer Science. Engineers with a BSc in Computer Science can also make a smooth switch to this field with 2-3+ years of experience.

This role is a an outstanding opportunity within J.P. Morgan, and will offer the candidate the opportunity to join a high profile efficient team and take a partnership role within the Firm Data Management group, to support one the most significant change programs at J.P. Morgan Chase.