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 opportunitiesWorking 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 teamsGiven 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 fieldStrong analytical/modelling skills and business orientation with proven ability to use data and analytics to drive business results; strong technical backgroundDemonstrated experience working within a data science teamTimeseries analysis and modellingTraining and fine-tuning of the ML model for investment modelsStrong 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 teamsWriting production quality code, unit testing and familiarity with version control Familiarity with cloud-based technologiesDemonstrated experience using alternative datasets in investing and alpha researchIn-depth understanding of financial markets requiredStrong communications skills and the ability to present findings to a non-technical audiencePassion 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 roleFront office experience in finance (preferably buyside)Familiarity in incorporating unstructured data into investment researchKnowledge of alternative data landscapeCFA