Intern, Data Science and Optimization

Fidelity-posted about 2 years ago
Intern
Boston, MA
5,001-10,000 employees
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The Fidelity Enterprise Services Advanced Technology for Investment Management Team contributes to the vitality and growth of the organization by transforming breakthrough technologies into practical capabilities for Fidelity’s internal and external investment clients. The Team promotes companywide collaboration while delivering new Artificial Intelligence enabled portfolio level perspectives to investment managers and client service colleagues. Fidelity is looking for an energetic and innovative intern who brings hands-on data science capabilities in research and development of AI/ML methods as components in consolidating investment management technology solutions. It will be important for a candidate to be curious, creative, and agile in learning and applying investment concepts.

  • Advancing the research and development of AI/ML methods as components in the delivery of innovative investment management technology solutions
  • Designing and implementing portfolio risk and optimization techniques to deliver industry differentiated capabilities
  • Effective partnering across Fidelity’s technology, AI Center of Excellence and investment teams
  • Graduate degrees in computer science, computational financial engineering or related fields
  • 2+ years of academy course/project training on machine learning, optimization, data science and related fields
  • Demonstrated success development of large-scale computing algorithms with Java, Scala, Python or R with GPUs and/or map-reduce framework on SPARK cluster
  • Proven success building machine learning models to solve real-world problems
  • Proficient in programming languages including Python and/or R, C/C++, Java/Scala
  • You have passion for the financial markets, products, and processes (including: Fixed Income Instruments/Analytics, Asset Pricing Models/Instruments and Multi-Factor Risk Models)
  • You have professional knowledge with statistical models, predictive models and time series analysis (such as regression, classification, simulation, dimension reduction)
  • You have solid mathematical background of solving common optimization problems (including: linear/nonlinear/integer programming)
  • You have hands-on experience in developing and evaluating machine learning models on large scale datasets
  • You have meticulous attention to detail and unquestioned integrity
  • You are a fast learner and a good team player
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