Staff Data Scientist

Sift

Staff Data Scientist developing advanced modeling strategies for fraud prevention at AI-powered platform Sift. Focusing on statistical innovation while ensuring model quality against adversarial dynamics.

Posted 6/8/2026full-timeRemote • California • 🇺🇸 United StatesLead💰 $195,000 - $265,000 per yearWebsite

About the role

Key responsibilities & impact

Architect and own advanced modeling strategies across fraud and abuse problem domains.
Establish and defend model quality standards that account for adversarial dynamics.
Lead statistical innovation on highest-leverage fraud problems.
Partner with ML engineering and information security on adversarial robustness.
Build automated workflows that scale human expertise while respecting fraud complexity.

Requirements

What you’ll need

5+ years of hands-on modeling experience with production accountability.
Deep, hands-on knowledge of fraud and information security patterns.
Deep expertise in multiple modeling paradigms: Tree-based methods (XGBoost, LightGBM), deep learning architectures (CNNs, RNNs, transformers), and graph-based methods.
Advanced degree in Statistics, Data Science, Machine Learning, or equivalent.
Proven ability to partner with AI-assisted automation tools.
Comfort working in ambiguity and adversarial contexts.

Benefits

Comp & perks

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Applicant Tracking System Keywords

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Hard Skills & Tools

modeling strategiesstatistical innovationTree-based methodsXGBoostLightGBMdeep learning architecturesCNNsRNNstransformersgraph-based methods

Soft Skills

leadershippartneringworking in ambiguity

Certifications

advanced degree in Statisticsadvanced degree in Data Scienceadvanced degree in Machine Learning