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Asset & Wealth Management – Intelligent Digital Solutions – Big Data and Analytics – Associate – New York, NY

Req #: 180016208
Location: New York, NY, US
Job Category: Digital
Job Description:
J.P. Morgan Intelligent Digital Solutions (IDS) is a newly developed division of J.P. Morgan Asset & Wealth Management – one of the largest asset and wealth mangers in the world, with client assets of $2.7 trillion and assets under management of $1.9 trillion (Assets as of Sept. 30, 2017). 
 
The IDS Big Data and Analytics team will primarily focus on using statistical analysis, modeling techniques, and deep learning methods to drive innovative solutions for data-driven investment insights, improved client engagement, and operational effectiveness.  This is an exciting opportunity to join a small, dynamic team with the resources and impact of one of world’s largest companies. We are looking for motivated individuals to push the boundaries of what’s possible in Asset and Wealth Management.
 
What You Can Expect
To work alongside our top tier professionals, including data scientists, investment professionals, and marketing analytics teams, driving product innovation and identifying opportunities to incorporate machine learning into J.P. Morgan Asset & Wealth Management.  Your responsibilities may include:
  • Performing analysis on our proprietary, unique dataset to identify new insights
  • Operating and proposing  enhancements to the data science platform and architecture
  • Building prototype models with data pipelines that serve as roadmap to production
  • Facilitating data visualization to help drive decision making
  • Marketing real-world, commercial recommendations through effective presentations to various stakeholders
About You
We're looking for problem-solvers with a passion for developing innovative solutions!
 
Qualifications:
  • Master’s Degree or PhD, preferably in computer science, statistics, or other quantitative fields
  • 2+ years of experience in applying statistical methods to large data sets and building predictive models
  • Preference in participation in data science training, fellowship, or bootcamp programs
  • Strong programing skills and data analysis proficiency, such as Python (numpy/pandas/scikit-learn), R, Java, C++, Scala, SQL, Matlab
  • Experience with major deep learning libraries (e.g. TensorFlow, Torch, DeepLearning4J, etc.)
  • Participation in Kaggle competition or equivalent highly desirable
  • Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience
  • Authorization to work permanently in the U.S.
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