Data Scientist – New York, NY

Data Scientist

The Quantitative Services Innovations Professional will assist in software development and operational support of a reconciliation and machine learning based platform. This platform performs highly customizable reconciliations using innovative matching techniques including fuzzy logic and supervised learning-based machine learning techniques. The project has tight deliverable timelines and will require the right person to work with multiple teams within the bank including business partners, technology teams and operations groups. This role will also include participation in all phases of Machine Learning based projects built by our team including model development, model validation, governance and maintenance.


    • The candidate is expected to work closely with the business analysts, business partners and other technology partners to gather requirements and successfully build, test and implement software solutions.
    • Work with operations and business personnel to provide support for the recon process including new user onboarding.
    • Assist analyst and end-users with applying mathematical matching algorithms to their problem statements.
    • Use proprietary and open source machine learning libraries for developing supervised learning based solutions.
    • Be engaged in full lifecycle of a machine learning project including model development, governance, and maintenance.


  • University degree or higher in Computer Science, Mathematics, Financial Engineering, Economics or related quantitative field
  • 2+ years relevant industry experience
  • Python programming experience
  • Experience or formal training with machine learning models
  • Strong technical background with proven experience working in an Agile software development lifecycle
  • Experience with database technologies
  • Experience with Excel/VBA

Discover More AI Jobs:


More Information

Apply for this job Apply via Facebook
Share this job

We are one of the largest AI Communities online. Our publications have over 8.5 Million Views Annually and we have over 120K subscribers.