AI-Powered Fraud Analytics Data Scientist

DataVisor; Mountain View (CA); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Equity options

Medical, dental, and vision

401(k)

DTO + holidays

Research opportunities

Team-building events

Job summary

DataVisor is seeking a hands-on Data Scientist to own the detection strategy for its AI-powered Fraud and AML platform. You will design detection logic, thresholds, and false-positive tradeoffs across RTP, ACH, Wire, Check, and Onboarding, while solving the Cold Start problem for new clients.

You will also configure the platform, stand up tenants for demos, and write technical documentation for clients and teams. Proficiency in Python and SQL is essential, with a focus on risk judgment.

Qualifications

• BS or MS in Statistics, Mathematics, Computer Science or related quantitative discipline.
• At least 1 year of full-time experience in fraud strategy, AML or risk analytics.
• Working knowledge of fraud/AML typologies and payment rails (RTP, ACH, Wire).

Responsibilities

• Design and back-test detection strategies for RTP, ACH, Wire, Check and Onboarding.
• Translate typologies into concrete detection logic and thresholds.
• Address Cold Start for new clients with evolving data.
• Configure the platform, write client documentation, and support demos.
• Collaborate with Product, Data Science, Engineering and GTM teams.

Skills

Python

SQL

Pandas/Numpy/Scikit-learn

Education

BS in Statistics/Mathematics/CS

MS preferred

Tools

Python

SQL

Job description

DataVisor is seeking a hands-on Data Scientist to own the detection strategy for its AI-powered Fraud and AML platform. You will design detection logic, thresholds, and false-positive tradeoffs across RTP, ACH, Wire, Check, and Onboarding, while solving the Cold Start problem for new clients.

You will also configure the platform, stand up tenants for demos, and write technical documentation for clients and teams. Proficiency in Python and SQL is essential, with a focus on risk judgment.