Senior Data Scientist, Fraud

Unchain Data; Menlo Park (CA); On-site; USD 187,000 - 220,000; Full time

Benefits offered by this job

100% paid health insurance

401(k) matching

Flexible benefits spending account

Employee equity ownership

Catered meals and events

Job summary

Unchain Data is seeking a Senior Data Scientist in Menlo Park to design and deploy machine learning models that enhance fraud detection and protect users. This pivotal role will require collaboration across teams to influence system architecture and ensure data-driven policies.

As a candidate, you should have 5+ years of experience in data science, proficiency in Python and SQL, and a strong understanding of fraud detection methodologies. The position offers a competitive salary and comprehensive benefits.

Qualifications

• 5+ years of experience in data science or applied ML with a focus on fraud detection.
• Advanced proficiency in Python and SQL.
• Strong statistical acumen with experience in anomaly detection.

Responsibilities

• Design and deploy fraud detection models.
• Analyze behavioral data for emerging fraud vectors.
• Develop robust data pipelines to ensure model reliability.

Skills

Python

SQL

Machine Learning

Anomaly Detection

Statistical Analysis

Tools

XGBoost

LightGBM

TensorFlow

Job description

About the Role

The Fraud Data Science team safeguards Robinhood and its customers by detecting and preventing fraud and abuse across our platform. We leverage machine learning and analytics to combat malicious behavior in real time, supporting a safe and trusted experience for all users. Our work has direct impact on customer security, company risk posture, and regulatory compliance.

As a Senior Data Scientist on the Fraud team, you will own the design and deployment of ML solutions that proactively surface suspicious activity, reduce financial loss, and improve fraud detection precision. You'll collaborate closely with engineering, product, risk, and compliance partners to influence system architecture, shape policy through data, and enhance the safety and integrity of our platform.

This role is based in our Menlo Park office, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

Responsibilities

• Design and deploy fraud detection models to protect Robinhood users and assets in real time
• Analyze behavioral data to uncover emerging fraud vectors and support rapid incident response
• Develop robust data pipelines and monitoring systems to ensure model accuracy and reliability
• Partner with engineering and product teams to implement safeguards and user-facing features
• Guide experimentation strategy and contribute to long-term fraud prevention roadmap

Requirements

• 5+ years of experience in data science or applied ML, with a focus on fraud detection or risk mitigation
• Advanced proficiency in Python and SQL; experience with ML frameworks like XGBoost, LightGBM, or TensorFlow
• Strong statistical acumen with experience in anomaly detection, pattern recognition, and A/B testing
• Excellent communication skills and ability to influence decision-making across technical and non-technical audiences
• A collaborative mindset and proactive approach to navigating ambiguity in fast-paced environments

Benefits

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
• Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
• Lifestyle wallet—a highly flexible benefits spending account for wellness, learning, and more
• Employer-paid life and disability insurance, fertility benefits, and mental health benefits
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
• Exceptional office experience with catered meals, events, and comfortable workspaces

Compensation

In addition to the base pay range listed below, this role is also eligible for bonus opportunities, equity, and benefits.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)

$187,000–$220,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)

$165,000–$194,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)

$146,000–$172,000 USD