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Responsibilities:
- Build, validate, and deploy machine learning models to identify and prevent fraud in real time.
- Support reproducibility and robustness of models through documentation, testing, and monitoring.
- Collaborate with Risk Strategy and Engineering to optimize model inputs and deployment.
Qualifications:
- 5+ years of experience analyzing large datasets, with 3+ years of ML experience.
- Proficiency in SQL and Python for statistical modeling and machine learning.
- Experience deploying and monitoring ML models in production.
Ideal Qualifications:
- 1+ years of relevant risk experience.
- Familiarity with LLMs or GenAI for risk detection.
- Experience with modern data tools like dbt and model governance in regulated industries.
Total Rewards:
- Competitive base salary and equity (stock options/RSUs).
- Comprehensive benefits package.
- Commitment to diversity and inclusion.
Mercury
Mercury is a fintech company that provides banking services for startups. They are an equal opportunity employer committed to diversity and inclusion.