Senior Data Scientist, Predict

Alloy

New York City, New York, US
Base: $212,000 - $251,000; bonus/equity: employee ...
Hybrid (on-site three days a week with remote work on mondays and fridays)
Machine learning models at scale
Highly imbalanced datasets
Python and sql proficiency
Alloy is seeking a Senior Data Scientist for their Predict team in New York City to enhance fraud detection through real-time machine learning systems. The ideal candidate will have extensive experience in applied fraud research and machine learning, and will be expected to work on complex datasets while collaborating with cross-functional teams

Job Summary

  • The Predict team builds Alloy’s real-time machine learning systems at scale, focusing on fraud detection to make decision-making smarter, faster, and more adaptive.
  • You will contribute to the design, training, and evaluation of machine learning models, develop testing plans, and support production ML workflows.
  • Alloy offers unlimited PTO, employee stock options, comprehensive medical benefits, a 401k match, and a hybrid work environment with catered lunches.

Matching Summary

Match Score: 85

Alloy is seeking a Senior Data Scientist for their Predict team in New York City to enhance fraud detection through real-time machine learning systems. The ideal candidate will have extensive experience in applied fraud research and machine learning, and will be expected to work on complex datasets while collaborating with cross-functional teams.

Salary

Base: $212,000 - $251,000; Bonus/Equity: Employee stock options; Benefits: Competitive total benefits package

Skills & Requirements

Must-have

  • Machine learning models at scale
  • Highly imbalanced datasets
  • Python and SQL proficiency
  • Processing billions of records
  • Fraud detection expertise

Nice-to-have

  • Financial fraud detection experience
  • Modeling on graph structures
  • Experience with BI tools like Looker

Key Requirements

  • 8+ years in Applied Fraud Research, Data Science, or Machine Learning
  • Client-facing capacity experience
  • Experience with tree-based models
  • Experience developing metrics and dashboards
  • Local to Greater New York City

Work Rights

Not specified

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