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Machine Learning Engineer
2 months ago
We are seeking a highly skilled Machine Learning Engineer to join our team at Robinhood, a leading fintech company that's democratizing finance for all. As a Machine Learning Engineer working on Fraud and Risk, you will play a key role in shaping our vision, structures, and systems to mitigate risks to our business.
Key Responsibilities- Design and develop machine learning systems to power fraud prevention and risk reduction efforts at Robinhood.
- Build production-grade models on large-scale datasets to measure effectiveness across products.
- Collaborate with cross-functional teams to implement insights and analytical solutions to empower data-driven decision making.
- Work with the data team and partner marketing, product, content, and design teams to build data solutions and products to drive user and revenue growth.
- Familiarity with fraud domains and banking processes, including account takeover, ACH fraud, debit/credit card fraud, first-party fraud, and synthetic identity fraud.
- Demonstrated expertise in building and deploying fraud models using large datasets, with a strong track record of success in fraud detection and prevention.
- Knowledge of model risk governance and experience collaborating with model validation teams to ensure compliance with regulatory requirements.
- Graduate degree in a quantitative field such as mathematics, economics, statistics, engineering, or natural sciences (or equivalent research experience).
- Solid understanding of unsupervised learning, statistical analysis, and machine learning algorithms for imbalanced datasets.
- Excellent programming skills, including familiarity with either Python (numpy, scipy, pandas) or R programming languages.
- Experience with Tableau, Looker, and/or Mode.
- Experience communicating data-driven insights.
- 2+ years of professional experience as a Machine Learning Engineer.
- 1 year of experience working in a research setting in an academic or commercial setting.
- Passion for working and learning in a fast-growing company.
- Strong customer empathy.
- Intense sense of curiosity.
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 salary range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones.
This role is also eligible to participate in a Robinhood bonus plan and Robinhood's equity plan. For other locations not listed, compensation can be discussed with your recruiter during the interview process.
