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Senior Machine Learning Data Scientist

1 month, 3 weeks ago
United States
Full-time
Senior
Data Scientist
Data Science and Analytics
AWS Feature Engineering Machine Learning Python PyTorch SageMaker Scikit-learn SQL XGBoost
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Extend

Extend

Extend is a technology company that offers powerful product and shipping protection solutions to merchants, helping them generate revenue and enhance customer loyalty. Their modern and cost-effective services provide a win-win situation for both busine...

Air Freight & Logistics
251-1K
Founded 2019
View All Jobs 11

Description

  • Own the end-to-end machine learning model lifecycle, including requirements, experimentation, development, evaluation, and model cards.
  • Partner with ML engineers to deploy models and support production infrastructure.
  • Translate fraud patterns into machine learning solutions by defining what to model and how success should be measured.
  • Design and maintain feature engineering pipelines for model development.
  • Monitor model performance in production, track drift, and determine when retraining is needed.
  • Collaborate with leadership, go-to-market, fraud operations, product, and engineering teams to execute fraud strategies.
  • Work closely with Product, Engineering, and Fraud Intelligence to turn complex data into scalable ML systems.
  • Champion continuous learning, experimentation, and collaboration across the fraud and data science teams.

Requirements

  • Bachelor’s degree or higher in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Operations Research, Physics, or a related field.
  • 3+ years of experience building and deploying machine learning systems into production.
  • Strong proficiency in Python and SQL.
  • Strong understanding of ML fundamentals, including model selection, evaluation methodology, feature engineering, and common failure modes.
  • Hands-on experience with PyTorch, scikit-learn, and XGBoost or similar gradient boosting frameworks.
  • High attention to detail, intellectual curiosity, and a deep understanding of user behavior and fraud patterns.
  • Empathetic, humble, and collaborative team player.
  • Must be located within the continental United States.
  • Experience building fraud detection or risk assessment systems is preferred.
  • Experience with cloud ML platforms, especially AWS such as SageMaker, is preferred.
  • Experience with graph data and graph-based models such as PyTorch Geometric is preferred.
  • Experience with model monitoring and observability tooling such as Arize is preferred.

Benefits

  • Estimated pay range of $135,000 to $165,000 per year.
  • Full medical, dental, and vision benefits.
  • Stock equity in an early-stage, fast-growing startup.
  • Generous, flexible paid time off policy.
  • 401(k) with Financial Guidance from Morgan Stanley.
  • Collaborative and supportive team environment.

Interested in this position?

Apply directly on the company website

Apply Now

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