Senior Associate, Data Scientist

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Date: May 11, 2019

Location: New York, NY, US

Company: New York Life Insurance Co

New York Life Investments (NYLIM), an indirect, wholly owned subsidiary of New York Life Insurance Company, is a top 25 global asset management firm. With more than $500 billion in assets under management, NYLIM is a premier investment management firm serving a variety of client segments including retail, institutional, insurance and defined contribution and benefit on a global basis. New York Life Investments offers a diverse set of investment capabilities ranging from traditional equity and fixed income to alternative investment strategies and multi-asset solutions. Renowned for its premier investment acumen and client focus, NYLIM’s vision is to be one of the most trusted providers of investment management expertise and long-term financial security.

 

We are looking for a full stack Data Scientist to join New York Life Investment Management’s Business Intelligence & Analytics (BI&A) team.  The BI&A team is a stand-alone center of excellence supporting our Retail Investment Management business across Distribution, Marketing, Service and Senior Management.  We partner with and support each area, leveraging data to drive business strategy, decision making and support of our distribution efforts.

This role requires an individual with a strong sense of ownership, technical and analytical expertise as well as the ability to effectively interact with both business and IT teams.  The person in this role will be a data expert who will build and grow data science product/platform that enable better analytics across our data-driven organization.

 

Responsibilities:

  • Identify, analyze, and interpret trends or patterns in complex data sets and develop graphs, reports, visualization and presentations of results and insights
  • Responsible for research, delivery, implementation and support of data and analytical solutions
  • Work on end-to-end model development; Use cutting-edge tools and machine learning techniques to develop propensity models, recommendation engines, client segmentation etc.
  • Design and develop data marts, model pipelines, automated workflows, and analytical processing solutions in big data ecosystems

Qualifications:

  • Master’s degree with 3+ years’ experience required, PhD preferred, in a quantitative discipline (Computer Science, Mathematics, Statistics, Economics, Physics, Engineering or related discipline
  • Financial industry experience a plus
  • Strong experience in Big Data processing using Spark, Hive, shell scripting, etc.
  • Proficiency in SQL and one of Python/R for programming and modeling
  • Strong data visualization skills for "story-telling" through data; Experienced in Tableau a plus
  • Knowledge of machine learning algorithms and model development
  • Strong analytical, problem-solving and organizational skills; Attention to detail a must
  • Strong communication skills
  • Ability to build relationships and work effectively with diverse stakeholders at all levels
  • Ability to work efficiently in a fast-paced environment

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