热门公司

招聘

职位Robinhood

Senior Data Scientist, Fraud

Robinhood

Senior Data Scientist, Fraud

Robinhood

Menlo Park, CA

·

On-site

·

Full-time

·

1mo ago

必备技能

Python

SQL

TensorFlow

Spark

Machine Learning

Join us in building the future of finance.

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

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(s), with in-person attendance expected at least3 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.

What you’ll do

  • 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

What you bring

  • 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 Tensor Flow

  • 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

What we offer

  • 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 & 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.

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

Base Pay Range:

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$187,000—$220,000 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$165,000—$194,000 USDZone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$146,000—$172,000 USD
Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

总浏览量

0

申请点击数

0

模拟申请者数

0

收藏

0

关于Robinhood

Robinhood

Robinhood

Public

Democratizing finance for all.

1,001-5,000

员工数

Menlo Park

总部位置

$32B

企业估值

评价

3.7

10条评价

工作生活平衡

3.2

薪酬

3.5

企业文化

4.1

职业发展

3.0

管理层

2.8

65%

推荐给朋友

优点

Great team culture and collaborative environment

Flexible hours and work-life balance

Innovative projects and cutting-edge technology

缺点

Management issues and lack of direction

High pressure and stressful environment

Long hours and overwhelming workload

薪资范围

42个数据点

Junior/L3

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L1

0份报告

$147,000

年薪总额

基本工资

-

股票

-

奖金

-

$124,950

$169,050

面试经验

4次面试

难度

3.5

/ 5

时长

21-35周

体验

正面 0%

中性 50%

负面 50%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience