Staff Data Scientist — Real-Time Fraud ML Lead

Mercury; New York (NY); On-site; USD 239,000 - 299,000; Full time

Job summary

Mercury is seeking a Machine Learning-focused Data Scientist to bolster our Risk team's fraud defenses and customer insights. You will build and deploy ML models in real time, validate their robustness, and ensure data quality across pipelines.

You’ll also lead initiatives, partnering with Risk Strategy and Engineering to optimize model inputs and deployment. Ideal candidates have extensive Python and SQL experience, prod ML deployment, and a track record of uplifting peers while aligning

Qualifications

• 7+ years of experience modeling and analyzing large datasets.
• 5+ years focused on machine learning and statistical modeling.
• Proficiency in SQL to understand and manage imperfect data.
• Strong Python skills and experience deploying ML models.
• Ability to lead, empower others and align cross-team roadmaps.

Responsibilities

• Build, validate, and deploy real-time fraud-detection ML models.
• Document, test, and monitor models for reproducibility and robustness.
• Ensure data quality across pipelines and tools.
• Collaborate with Risk Strategy and Engineering on inputs and deployment.
• Prototype and codify best practices, uplifting the team.

Skills

SQL

Python

ML modeling

Production deployment

Leadership

Strategic alignment

Tools

dbt

Job description

Mercury is seeking a Machine Learning-focused Data Scientist to bolster our Risk team's fraud defenses and customer insights. You will build and deploy ML models in real time, validate their robustness, and ensure data quality across pipelines.

You’ll also lead initiatives, partnering with Risk Strategy and Engineering to optimize model inputs and deployment. Ideal candidates have extensive Python and SQL experience, prod ML deployment, and a track record of uplifting peers while aligning