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Lead Data Scientist

Salary undisclosed

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A leading FinTech business is looking to hire a Lead Data Scientist to join a growing team.

Salary: $140,000 - $180,000

Location: New York

Work type: Hybrid (3 days in office)

The role will look to bridge data science with product development, creating dynamic synergies. Combining expertise in machine learning, AI, advanced statistical modeling, and big data, with deep domain knowledge, we deliver comprehensive solutions that keep our clients ahead in a rapidly evolving landscape.

Lead Data Scientist Role

  • Collaborate with product teams and fellow scientists to identify new AI/ML opportunities within our content and products.
  • Research and implement AI/ML algorithms to address business challenges, delivering solutions as microservices in partnership with content and product engineering teams.
  • Contribute to the development and enhancement of our common data science platform.
  • Stay current on AI/ML advancements and deliver periodic presentations to internal teams on these trends.

Key Requirements:

  • 6+ years of experience in developing AI/ML applications and data-driven solutions.
  • Graduate degree in Computer Science, Engineering, Statistics, or a related field, or equivalent work experience.
  • Expertise in Natural Language Processing (NLP), Deep Learning, Generative AI, and other state-of-the-art AI/ML techniques.
  • Strong understanding of computer science fundamentals, computational complexity, and algorithm design.
  • Experience in building large-scale distributed systems in an agile environment, with the ability to quickly prototype solutions.
  • Proficiency in high-level programming languages (Python, Java, C++) and data science libraries (Pandas, NumPy, etc.).

Preferred Qualifications:

  • M.S. in Computer Science with a focus on AI/ML research, with publications in top-tier journals or conferences.
  • Experience working within Fintech, Financial Services or Insurance
  • Experience with AWS, particularly ML workflows using SageMaker, serverless computing, and storage solutions such as S3 and Snowflake