Staff ML Risk Analytics

About the role

This role focuses on leveraging machine learning to combat fraud within Coinbase. The work involves developing and implementing ML data and feature strategies, as well as managing the entire feature engineering pipeline. Success in this position means effectively diagnosing and addressing gaps in existing tooling infrastructure to improve fraud detection capabilities.

The Staff ML Risk Analytics professional will collaborate closely with Machine Learning Engineers to transition insights into functional ML systems. This includes setting technical direction for the ML Analytics function and providing mentorship to less experienced team members. The role also requires cross-functional partnerships with Product Managers and Risk analysts to ensure comprehensive solutions.

A key aspect of this position is acting as a knowledge resource for the team regarding advancements in the ML industry. The ideal candidate will bring a deep understanding of ML evolution and apply this expertise to continually refine fraud prevention methods. This ensures Coinbase remains at the forefront of protecting its systems from abuse.

The base salary for this position ranges from $98,000 to $162,000, with total compensation potentially including equity, bonuses, and benefits.

Skills that matter here

• machine learning: This role requires applying machine learning techniques to detect and prevent fraud.
• data science: The position involves using data science principles to analyze information and build predictive models for risk.
• Spark: Expertise in Spark is needed for processing and analyzing large datasets to support ML models.
• Python: Python is a core language for developing and implementing machine learning solutions and feature engineering pipelines.
• big data: The role involves working with big data environments to manage and process the extensive data required for fraud detection.
• SQL: SQL skills are necessary for querying and manipulating data to support ML analytics and feature generation.

Who this role suits

• A person with a strong background in machine learning analytics, specifically within risk or payments.
• Someone who enjoys defining technical direction and mentoring junior team members.
• An individual who is passionate about combating fraud and abuse through data-driven solutions.
• A professional who can effectively partner with various teams, including product and engineering, to deliver solutions.

From the employer

What you’ll be doing:

• Define the ML data and feature strategy for fraud detection.
• Own the end-to-end feature engineering pipeline.
• Diagnose gaps between current tooling infrastructure and needed solutions.
• Partner with Machine Learning Engineers to translate insights into production-ready ML systems.
• Set technical direction for the ML Analytics function and mentor junior team members.
• Partner cross-functionally with Product Managers and Risk analysts.
• Serve as the team's institutional knowledge resource on ML industry evolution.

What we look for in you:

• 8+ years of hands-on experience in machine learning analytics or related fields.
• Deep expertise in Spark, Python, and big data ML.
• Proven experience in feature engineering for ML models.
• Holistic understanding of ML industry evolution.
• Background in risk or payments ML is strongly preferred.
• A passion for fighting fraud and abuse.
• Ability to responsibly use generative AI tools in workflows.

What we offer:

• Base salary range: $98K - $162K.
• Total compensation may include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)).
• Equal Opportunity Employer commitment.
• Reasonable accommodations for individuals with disabilities.