This position may no longer be available
Posted . It may have been filled, expired, or closed.
This position may no longer be available
Posted . It may have been filled, expired, or closed.
Type
FULL TIME
Work Style
On-site
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.
The Data Intelligence sub-team safeguards ecosystem by turning market, trading, and customer signals into high-confidence intelligence. Our work is critical to ensuring the integrity of the platform — from detecting anomalies and supporting compliance to shipping well-governed data products and machine learning features. We partner across functions to deliver proactive, data-driven decisions that protect our users and the business!
As a Data Scientist, you'll drive the development of real-time fraud detection models, analyze behavioral data to surface risks, and shape the future of fraud prevention through experimentation and robust data pipelines. Your work will play a pivotal role in shielding customers from harm and enabling trustworthy financial experiences.
The role is located in the office location(s) listed on this which will align with our in-office working environment. Please connect with your recruiter for more information regarding our in-office philosophy and expectations.
Design and deploy fraud detection models to protect 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
3+ 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
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.
Prepare for your Data Scientist interview at Robinhood.