Staff ML Risk Analytics

About the role

In this role, you will define the machine learning data and feature strategy specifically for fraud detection. You will manage the end-to-end feature engineering pipeline and work with Machine Learning Engineers to implement production-ready systems.

Success in this position involves setting the technical direction for the ML Analytics function while mentoring junior members. You will collaborate with Product Managers and Risk analysts, ensuring that the team stays informed about the latest developments in the ML industry.

The listed salary range reflects the base compensation for this role, with additional potential for equity and bonuses.

Skills that matter here

• machine learning: This role requires deep expertise in machine learning to enhance fraud detection capabilities.
• data science: Data science skills are essential for defining strategies and analyzing data related to fraud.
• Spark: Proficiency in Spark is necessary for handling big data in machine learning projects.
• Python: Python will be used extensively for developing and implementing ML models.
• big data: Experience with big data is crucial for managing large datasets in fraud analytics.
• SQL: SQL skills are important for querying and managing data effectively.

Who this role suits

• A candidate with over 8 years of experience in machine learning analytics or related fields.
• Someone who has a strong background in risk or payments machine learning is preferred.
• A person who is passionate about combating fraud and can responsibly integrate generative AI tools into their work.
• An individual who is comfortable mentoring junior team members and collaborating cross-functionally.

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.