[Hiring] Staff Data Scientist @Mercury

Role Description

We are hiring a Machine Learning-focused Data Scientist to support our Risk team. This team is responsible for detecting, monitoring, and mitigating both first- and third-party fraud while ensuring we know and understand our customers and monitor 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.

This is an opportunity to join Mercury at a pivotal moment in our growth. You’ll be working on some of the most critical challenges facing the business and collaborating across product, engineering, and risk to protect our customers and the financial system at large.

• 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 to optimize deployment and observability
• Act as a technical lead prototyping, iterating on, and codifying best practices - and bringing the rest of the team along

Qualifications

• 7+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 5+ 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
• Demonstrated ability to lead and empower others, delivering not just on your own work, but upleveling those around you
• The ability to drive strategic alignment between teams with differing roadmaps, timelines, or architectures

Requirements

• 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

Benefits

• Total rewards package includes base salary, equity (stock options/RSUs), and benefits
• Highly competitive salary and equity ranges within the SaaS and fintech industry
• New hire offers are based on experience, expertise, geographic location, and internal pay equity
• Target new hire base salary ranges for this role:
• US employees (any location): $239,000 - $298,800 USD
• Canadian employees (any location): $225,900 - $282,400 CAD