Head of Machine Learning - Application Fraud

@glc β€’ United State
Remote
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AI Summary

Lead a high-performing team of Data Scientists, manage production machine learning systems, and drive business impact.

Key Highlights
Lead and mentor a high-performing team of Data Scientists
Manage production machine learning systems
Drive business impact
Key Responsibilities
Lead and mentor a high-performing team of Data Scientists
Grow the team from 2–3 to 5–6 engineers/scientists
Own the roadmap for a portfolio of production ML models
Drive projects from data acquisition and feature engineering through model development, deployment, monitoring, and continuous improvement
Technical Skills Required
Python Machine Learning
Benefits & Perks
Up to $260,000 Base + Competitive Equity
Fully Remote within the U.S.
High-growth, profitable Series B startup
Nice to Have
Leadership experience at a fast-growing startup
Strong career progression with increasing technical and leadership responsibility
Experience in fraud detection, identity verification, financial risk, or similar domains

Job Description


πŸš€ Head of Machine Learning – Application Fraud (Remote, U.S.)

πŸ’° Compensation: Up to $260,000 Base + Competitive Equity

I'm partnering with a well-funded, venture-backed AI/ML startup that has successfully scaled from early product-market fit into a rapidly growing business. The company is in the Series B stage, has secured backing from some of Silicon Valley's leading investors, serves major enterprise customers, and has already achieved profitability while continuing to grow. Their machine learning platform solves mission-critical problems in a high-stakes industry where accuracy, scalability, and real-time decision making are essential.

This is an opportunity to lead one of the company's most strategic machine learning teams, managing talented data scientists while remaining technically involved in the development of production machine learning systems.

Responsibilities

  • Lead and mentor a high-performing team of Data Scientists focused on production machine learning.
  • Grow the team from 2–3 to 5–6 engineers/scientists.
  • Own the roadmap for a portfolio of production ML models that directly impact the company's core products.
  • Drive projects from data acquisition and feature engineering through model development, deployment, monitoring, and continuous improvement.
  • Partner closely with Engineering, Product, and Executive Leadership to define technical strategy and deliver business impact.
  • Guide research into new problem areas and translate findings into production-ready solutions.
  • Write and review production-quality Python code when needed.
  • Present technical strategy, progress, and business outcomes to senior leadership.

βœ… Must Have

  1. 7–15 years of Applied Machine Learning or Data Science experience building production ML models in fintech, cybersecurity, or other high-stakes industries.
  2. 4+ years managing Data Science or Machine Learning teams in high-growth startups.
  3. Demonstrated success building and scaling multiple production ML models that solved complex, business-critical problems.
  4. Master's or PhD in Computer Science, Statistics, Mathematics, Physics, Engineering, or another STEM discipline.
  5. Strong experience across the complete ML lifecycle:
  • Feature Engineering
  • Model Training
  • Production Deployment
  • Monitoring & Continuous Improvement
  1. Excellent Python software engineering skills.
  2. Experience communicating technical strategy and results to senior leadership and business stakeholders.

⭐ Nice to Have

  • Leadership experience at a fast-growing startup (approximately 20–400 employees).
  • Strong career progression with increasing technical and leadership responsibility.
  • Experience in fraud detection, identity verification, financial risk, or similar domains.

Why Join?

  • πŸ’° Up to $260K base salary + competitive equity
  • 🌎 Fully Remote within the U.S.
  • πŸš€ High-growth, profitable Series B startup.
  • πŸ“ˆ Strong financial backing and long-term growth trajectory.
  • 🧠 Opportunity to lead mission-critical machine learning products with significant business impact.
  • πŸ‘₯ High-caliber engineering and data science team.



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