Data Scientist
Role details
Job location
Tech stack
Job description
We're building AI-driven applications that simplify customer workflows, starting with business onboarding. With our proprietary identity data and deep domain expertise, we're in a strong position to expand into a broader set of intelligent, risk-aware products., Design and ship production systems that detect and prevent fraud across KYB, trust & safety, and compliance workflows.
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Work with messy, real-world data Tackle problems with extreme class imbalance, sparse signals, evolving adversarial behavior, and limited ground truth.
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Leverage relationships in data Apply graph-based approaches and entity resolution techniques to uncover hidden connections and improve risk detection.
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Improve signal & labeling Use a mix of heuristics, weak supervision, and modern AI tools (including LLMs where appropriate) to generate better features and labels.
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Help scale our infrastructure Partner with engineering to build and evolve systems for feature generation, model training, and production deployment across multiple use cases.
Requirements
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4+ years of experience in fraud, risk, or trust & safety You've worked on real-world fraud or abuse problems and understand the domain deeply.
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Experience building and shipping production systems You've deployed models or data-driven systems that power external-facing products.
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Strong foundation in applied ML or data systems Comfortable working on classification problems with real-world constraints like imbalanced data, sparse signals, and changing patterns.
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Experience with graph or relational data approaches Familiarity with knowledge graphs, network analysis, or entity linking is strongly preferred.
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Hands-on and pragmatic You focus on impact over perfection and know how to balance speed, accuracy, and maintainability.