What are the responsibilities and job description for the Senior Data Scientist, Fraud Analytics and Strategy position at DataVisor?
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
Position Overview:
We are seeking a Senior Data Scientist to operate at the intersection of fraud domain expertise, analytics, and AI-driven product innovation. This high-impact IC role is for a hands-on strategist who will own fraud typologies end-to-end, drive detection strategy, and influence the evolution of our AI-powered platform.
The ideal candidate is a tactical visionary who translates complex fraud patterns into scalable defenses and partners with Data Science, Engineering, and Product teams to shape the future of fraud prevention.
Key Responsibilities:
- Lead the design, testing, deployment, and lifecycle management of fraud detection strategies across account origination, money movement, and card payment channels (CP/CNP).
- Conduct forensic analysis to identify emerging and “day-zero” fraud patterns, translating insights into actionable detection logic.
- Collaborate with the internal Data Science teams to refine ML features and ensure detection models capture the most relevant signals.
- Act as a key stakeholder for Engineering and Product teams, providing high-fidelity feedback on AI-driven tools and automation workflows.
- Own governance standards for fraud rules and ensure compliance with regulatory frameworks (AML, KYC, BSA).
- Serve as a subject matter expert on external data sources and enrichment signals to enhance detection capabilities.
- Mentor junior team members through project guidance and knowledge sharing.
- Partner with Product, Engineering, and Commercial teams to ensure fraud strategy aligns with evolving client and market needs.
- B.A./B.S. degree required in a quantitative or related field (STEM, Economics, Finance); advanced degree or professional certifications (CAMS, CFE) preferred.
- 3–5 years of hands-on experience in fraud strategy, fraud analytics, or risk management within Fintech, Tier-1 Banking, Payments, or large-scale Merchant environments.
- Strong proficiency in SQL and Python with experience analyzing large, complex datasets.
- Deep understanding of payment fraud (CP/CNP) and familiarity with AML, KYC, and regulatory frameworks.
- Ability to think like an attacker and proactively design robust fraud defenses.
- Experience collaborating cross-functionally with Data Science, Engineering, and Product teams.
- Strong communication skills to clearly convey technical and analytical findings to both technical and non-technical stakeholders.
PTO, Stock Option, Health Benefits
Annual salary range of USD $110,000 – $160,000, commensurate with experience.
Salary : $110,000 - $160,000