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Machine Learning Implementation Engineer at JP Morgan Chase (Jersey City, NJ)

As a Machine Learning Engineer, you will be responsible for building the infrastructure and implementing the algorithms developed by our ingenious data scientists and convert them to production ready models. You will be working on a cross-functional team with a Product Manager, UX designer, dev ops specialist, machine learning engineers, and software engineers. Youll be part of a team that is user focused, has a mentality for experimentation, and iterates quickly.

  • You have a strong foundation in Machine Learning and Computer Science and an understanding of applied statistics and math. You have a broad understanding of state of the art in Machine Learning.

  • You are a master of SQL-like databases (e.g. PostGres, Impala, Hive), preferably with experience with Spark and other big data platforms.

  • You are a proficient Python programmer and have at least some exposure to R. Regardless of your favorite scientific computing environment, you can flex between the two languages.

  • You have experience building production services and/or models, preferably as part of a product development team. A track record of implementing data-driven products is ideal.

  • You have worked in a collaborative development environment and have experience with continuous integration and delivery.

  • You can describe and speak in an approachable way about complex analyses and concepts within a cross-functional team. You are a great analytic translator.

  • Develop robust, scalable production data science products based on prototype algorithms developed in Python or Spark by the data science team. Youll evaluate trade-offs and do performance tuning for production traffic.

  • Iterate, and innovate on Machine Learning algorithms in collaboration with Machine Learning Engineers and Software Engineers

  • Collect, process and cleanse data from a wide variety of sources. Transform and convert unstructured data set into structured data for algorithm input.

  • Evaluate the effectiveness of user experiences, determining what data is needed and how to collect it

  • M.S. or Ph.D in Computer Science or relevant quantitative science

  • Minimum of 5 years in a data science engineering role

  • Experience working with product development teams and/or with developers

Our Consumer & Community Banking Group depends on innovators like you to serve nearly 66 million consumers and over 4 million small businesses, municipalities and non-profits.  Youll support the delivery of award winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers.
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