Lead and grow a high-caliber data science and ML team, build and scale production ML products end-to-end (feature engineering, training, deployment, monitoring), solve high-impact business problems in fintech/cybersecurity/financial risk, communicate results to executives, hire and mentor engineers, and drive technical strategy and operationalization.
Head of Data Science/ Machine Learning
Location : CA/Remote
Full time role
Education Requirements
- Preferred Master's or PhD in a relevant STEM field, but exceptional Bachelor's profiles considered.
Interview Process
- Four rounds: recruiter call, hiring manager interview, technical (coding and case study), and leadership round.
- Leadership round involves the head of people, CTO, and CEO.
Ideal Candidate Profile
- Combination of machine learning engineering and data science, capable of writing production code.
- Strong communicator, able to articulate complex information effectively.
Team Culture and Expectations
- High-caliber, select team with high expectations and visibility.
- Autonomy in growing products and scaling teams, with a strong focus on technical and problem-solving capabilities.
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
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
Experience in communicating progress + outcomes to senior management / stakeholders
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