Lead Data Scientist - Fraud model deployment Lead Data Scientist - Fraud model deployment …

Selby Jennings QRF
in San Francisco, CA, United States
Permanent, Full time
Last application, 22 Nov 21
USD180000 - USD200001 per year
Selby Jennings QRF
in San Francisco, CA, United States
Permanent, Full time
Last application, 22 Nov 21
USD180000 - USD200001 per year
Selby Jennings QRF
A very well-funded Fin-Tech firm is looking to enhance their fraud analytics group as they prepare to put new product offerings on the market for their customers. This firm has experienced substantial growth over the past several years and would offer unparalleled exposure coupled with long term job security. Our client is looking to leverage the latest in machine learning tools to expedite loan approval and provide more accuracy when it comes to customer predictions.

This role will be leading a small group within the data science domain to develop and enhance existing fraud identification and monitoring tools in an effort to track the performance of models and policies. This role will work with large alternative data sets and the latest in machine learning technology to develop various advanced analytics models. you will also partner closely with the data engineering teams to develop real-time model deployment platform, specifically in AWS.

This position will also offer 100% remote working flexibility.

Responsibilities:

  • Lead the development of data products and fraud models to identify and monitoring fraudulent threats
  • Build state-of-the art fraud monitoring tools in an effort to assure model performance and any necessary changes to strategies and existing policies.
  • Spearhead the development of end-to-end model development and deployment tools using cloud computing technologies (AWS preferred)
  • Effectively communicate and partner with third-party vendors.
  • Assure streamlined and positive customer experience with regards to fraud claims and investigations.
  • Provide various solutions to other areas of the business in an effort to drive profitability.

Requirements:

  • 5+ years of relevant industry experience (FinTech/ Alternative lending experience is a MUST)
  • Proven experience in a growing, fast-paced environment
  • 3+ years of hands on data engineering experience with cloud computing technologies
  • Previous experience developing machine learning models, specifically for Fraud ID and prevention.
  • Excellent written and verbal communication skills.
  • Masters or PhD degree in any STEM field of study is required.

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