
To support our Risk team, we are hiring a Machine Learning-focused Data Scientist. This team is responsible not only for detecting, monitoring, and mitigating both first- and third-party fraud but also ensuring we know and understand our customers while monitoring their behavior for financial crime risk. You’ll play a key role in strengthening our fraud defenses while ensuring that Mercury continues to deliver a smooth and trustworthy banking experience.
Here are some things you’ll do on the job:
- Build, validate, and deploy machine learning models to identify and prevent fraud in real time
- Support the reproducibility and robustness of said models through documentation, testing, and monitoring
- Ensure data quality and reliability across pipelines and tools
- Collaborate with Risk Strategy to ideate on model inputs and applications and with Engineering optimize deployment and observability
You should have:
- 5+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 3+ years of ML experience
- Proficiency in SQL and experience using it to understand and manage imperfect data
- Proficiency in Python and experience with statistical modeling and machine learning
- Experience deploying and monitoring machine learning models in production
- Comfort working in a fast-paced environment with evolving priorities
Ideally you also have:
- 1+ years of relevant risk experience
- Familiarity with LLMs or other GenAI and how they can be applied to risk or fraud detection
- Experience with modern data tools for pipelines and ETL (e.g., dbt)
- Experience with model governance as required in finance or other regulated industries
- Experience building zero-to-one solutions in ambiguous or greenfield problem spaces
Timezone overlap
UTC-8–-4
Open to
NA
Sign in to track applications and earn points.