Head of ML/Data Science
Why This Role Stands Out
This hybrid leadership role offers a unique opportunity to build and scale a critical ML/Data Science function from the ground up in a dynamic environment. You'll thrive here if you have a strong background in managing ML teams, a passion for developing innovative fraud detection models, and a desire to make a significant impact in a high-growth company. Embrace this chance to lead and grow your career.
Quick Overview
Job Description
Role Details
- Role: Head of ML, similar to a Senior Data Science Manager.
- Responsible for managing the application fraud team, building zero to one models, and running the suite of fraud products.
Technical and Experience Requirements
- Must have 4-5 years of management experience and have scaled products and teams.
- Needs to have hands-on coding ability, though they won’t code regularly, and must pass a technical coding exercise.
Education Requirements
- Preferred Master''s or PhD in a relevant STEM field, but exceptional Bachelor''s profiles considered.
Seniority
7 - 15 years of experience in applied ML/data science, building production models in fintech, cybersecurity, or other high stakes domains
Work experience
4+ years managing data science/ML teams in high-growth startups (must have managed people building and deploying ML products core to the business)
Proven track record of solving complex / high profile business problems with DS / ML solutions. (Scaled a product suite of ML models, not just one model)
Held senior/leadership role at a fast growing startup (20-400 people) with broad scope
Shows great slope and career progression
Education
Master''s or PhD in a STEM field (math, stats, CS, physics, engineering) - target top universities
Hard skills
End-to-end ML: feature engineering, model training, productionalization, monitoring
Strong software engineering abilities in Python
Domain experience in fraud, identity verification, or financial risk
Soft skills
Experience in communicating progress + outcomes to senior management / stakeholders
Skills
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