Senior Data Scientist (Fraud)

TL;DR

Senior Data Scientist (Fraud): Designing and deploying machine learning solutions to detect and prevent fraud across a high-scale financial platform with an accent on real-time anomaly detection and risk mitigation. Focus on building robust data pipelines, influencing system architecture, and collaborating with cross-functional partners to ensure platform integrity.

Location: Must be based in the US, with in-person attendance required at least 3 days per week at the Menlo Park office.

Salary: $146,000 – $220,000 USD (depending on location zone).

Company

A mission-driven fintech company dedicated to democratizing finance for all through innovative technology.

What you will do

• Design and deploy real-time fraud detection models to protect user assets.
• Analyze behavioral data to identify emerging fraud vectors and support incident response.
• Develop and maintain robust data pipelines and monitoring systems for model reliability.
• Partner with engineering and product teams to implement security safeguards.
• Guide experimentation strategy and contribute to the long-term fraud prevention roadmap.

Requirements

• 5+ years of experience in data science or applied ML, specifically in fraud or risk.
• Advanced proficiency in Python and SQL.
• Experience with ML frameworks such as XGBoost, LightGBM, or TensorFlow.
• Strong statistical acumen in anomaly detection, pattern recognition, and A/B testing.
• Excellent communication skills for influencing technical and non-technical stakeholders.
• Must be able to work in-person at the Menlo Park office at least 3 days per week.

Culture & Benefits

• Performance-driven compensation including bonuses and equity ownership.
• 100% paid health insurance for employees and 90% for dependents.
• 401(k) matching and lifestyle wallet for wellness and learning.
• Comprehensive life, disability, and mental health benefits.
• Generous time off including paid holidays, sick leave, and parental leave.