CIB Global Research - Data Science Manager

  • Competitive
  • New York, NY, USA
  • Permanent, Full time
  • JPMorgan.
  • 21 May 19

CIB Global Research - Data Science Manager

J.P. Morgan's Corporate & Investment Bank (CIB) isa global leader across banking, markets and investor services. The world's mostimportant corporations, governments and institutions entrust us with theirbusiness in more than 100 countries.

CIB Research
One of the world's most highly respected advisoryfranchises, J.P. Morgan fundamental and quantitative research providesthoughtful fundamental analyses for the world's largest public and privateinstitutional investors including: asset managers, pension funds, governments,hedge funds, and large corporations. Generating actionable ideas and thematicinsights that empower our clients to make well-informed investment and strategicdecisions.

Responsibilities

  • Buildand lead a Data Science team to support Global Research for the CIB
  • Design& implement granular domain-specific indicators from data, relating them tocompany, industry, and macroeconomic factors
  • Proposeand design investing strategies on economic predictions through multipleinvesting paradigms
  • Managerequirements for a set of dependent data products derived from a largeportfolio of integrated data feeds
  • Createdata sourcing strategy across multiple industry data verticals supporting ourprediction efforts
  • Generate a series of economic insights research reports relating trends in our indicators & predictions to investment themes
  • 5 years of experience in applied data analysis & prediction
  • Experiencein Analytics Leadership role. Capable of delivering practical data insights ina compelling manner actionable by senior leadership
  • ExpertPython programming experience
  • Strongexperience with Machine Learning APIs and computational packages (TensorFlow,Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels)
  • Experiencein an Analytics role in Financial Services beneficial but not mandatory
  • Bachelor's degree in relevant quantitative field (e.g.Statistics, Economics, Applied Math, Operations Research, other datascience fields), advanced degree or certification in the analytical fieldpreferred
  • Demonstrably strong data science modeling intuition and featureengineering creativity
  • Expertise in applying statistical techniques for time-seriesmeasurement/estimation and prediction
  • Strong written & verbal communication and presentation skills,with experience crafting a compelling narrative supported by data
  • A portfolio of open-data analyses or data-driven research publications would be ideal