Data Scientist, MBS Trading (Associate / VP)

  • Competitive for experienced Data Scientists
  • New York, NY, USA New York NY US
  • Permanent, Full time
  • Locke Careers
  • 14 Feb 18 2018-02-14

Our client, a global corporate and investment banking organization, is hiring a Data Scientist for its Mortgage-backed Securities (MBS) Quantitative Research team, here in New York. The new member of the team will have access to unprecedented proprietary data (loan and consumer data) and will be responsible for developing a new class of models, using machine learning, which will transform the business and provide insights to both internal and external clients. This is a newly created position.


Generally, responsibilities of the Quantitative Research team include new model specification, research, back-testing, and model implementation, as well as integration into products and production systems. The new member of the team will be responsible for leveraging big data and machine learning in the model development process.

Key responsibilities include:

  • Perform large-scale analysis on our proprietary data-set(s)
  • Identify new insights that drive feature modelling
  • Build prototype models with data pipelines that serve as road-map to production
  • Make real-world, commercial recommendations through effective presentations to various stakeholders
  • Leverages data visualization to communicate data insights and results
  • Document and test new/existing models in partnership with control groups
  • Implementation of models in proprietary C++ and Python libraries.
  • Work closely with technology on model integration with front end applications
  • Ongoing desk support


The role requires a combination of a structured approach to problem solving, a can-do mind set to data analysis and to work in a dynamic environment. Excellent communication skills are essential in our interaction with Sales, technology, and control functions.  A healthy interest in good software design principles is a requirement as well.

Key Qualifications:

  • A master’s or Ph.D. degree program in computer science, statistics, operations research or other quantitative fields
  • Strong technical skills in data manipulation, extraction and analysis
  • Fundamental understanding of statistics, optimization and machine learning methodologies
  • Mastery of software design principles and development skills using one of C++, Python, R, Java, Scala
  • Previous practical experience in solving machine learning problems using open-source packages
  • Participation in KDD/Kaggle competition or contribution to GitHub highly desirable
  • Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience