Apply Now    

Data/AI/Machine Learning - Software Engineer

Req #: 180020492
Location: Jersey City, NJ, US
Job Category: Technology
Job Description:

J.P. Morgan is a global leader in asset and wealth management services. The Asset Management line of business serves institutional, ultra-high net worth, high net worth and retail clients through its Global Investment Management and Global Wealth Management businesses. With client assets of $2.4 trillion and AUM of $1.7 trillion, we are one of the largest asset and wealth managers in the world.


J.P. Morgan Asset Management (Investment Management) is a leading investment manager of choice for institutions, financial intermediaries and individual investors, worldwide. With a heritage of more than two centuries, a broad range of core and alternative strategies, and investment professionals operating in every major world market, we offer investment experience and insight that few other firms can match.



JPMorgan Asset Management Technology is seeking a well-rounded hands-on data scientist that is experienced in building systems that support full Investment Management investment cycle with the main focus on Digital Platform. Deliver a next-generation platform for the Insights program, driven by Hibiscus analytics. Scope includes advanced quantitative analytics for Portfolio Insights, including risk factors and fund analysis, as well as launch and evolution of digital version of Portfolio Insights by leveraging Machine Learning/Artificial Intelligence techniques. Will be part of the high-caliber development team that works closely with the Front Office users on end-to-end solutions

  • Must be curious, hardworking and detail-oriented, motivated by complex analytical problems
  • Has to demonstrate interest in financial markets, and have ability to communicate directly with the business users
  • Should be able to work individually or as part of a global team to achieve project goals
  • Will interact closely with the product strategy and marketing teams to deliver a brand new customer-centric platform.
  • Will be responsible for full lifecycle: Coding, Compiling, Unit testing, integration, packaging and deployment of application software
  • Ensure overall quality of deliverables is consistent with defined standards and Agile development practice

Required Experience and Skills:

  • At least 3-years years of experience in a financial service environment with a focus in front-office applications.
  • Strong JAVA/.Net/C# or Python programming experience is required
  • Good understanding in data analysis (e.g. SQL) and other data paradigms
  • Solid financial engineering background is desirable
  •  Experience in machine learning areas such as recommendation systems, NLP, pattern recognition, predictive modeling, Artificial Intelligence
  • Experience implementing machine learning algorithms such as support vector machines, decision trees, logistic regression, clustering, neural networks, graphical models etc.
  • Experience visualizing data in Python (e.g. Bokeh) or a dashboard tool such as Tableau
  • Experience in front-office capital markets/investment management applications desired
  • Experience working with market Data Feeds a plus
  • Agile development experience or equivalent in fast-paced development environment
  • Solid communication and presentation skills


Other attributes:

CFA, FRM, and/or Financial Engineering degree and/or risk management knowledge is a major plus

Apply Now    
Link for schema

Join our Talent Community

Not ready to apply? Leave your information with us and we will keep you up to date with new career opportunities.

Other Information

Apply Using LinkedIn

You can also apply using your LinkedIn® profile. It may save you some time because your information will be automatically transferred into our system. Just click on the LinkedIn logo when you get to the application screen and follow the directions.

Submit an Updated Résumé

During the application process, be sure you have an up-to-date copy of your Résumé, your cover letter and any other documentation you would like to submit.