Head of Machine Learning

About the company

Our client is a fast-growing software company.

The role

Raydar is recruiting for this role on behalf of our client. Lead and expand a group of hands-on data scientists who develop and operate production machine learning models. Serve as a technical coach and as a partner to executives, product and engineering, setting priorities and delivering on tight schedules.

What you'll do

- Manage a small data science team and grow it over time as the work expands.

- Coach team members technically, reviewing details closely and giving clear guidance.

- Run planning, staffing and status updates with executives and cross-functional partners.

- Build commercial awareness and steer the team toward effective solutions under demanding deadlines.

- Own models across the whole lifecycle: data sourcing, feature design, labeling, training, experimentation, deployment and monitoring.

- Investigate emerging fraud patterns and shape new product offerings from what you learn.

- Improve model performance through iteration, new data sources and inventive feature work.

- Write dependable production code that supports real-time decisions for external partners.

- Produce and present analyses that guide data strategy, product direction, operational priorities, marketing and sales.

Requirements

What we're looking for

- Hands-on experience across the machine learning lifecycle, including feature work, training, deployment and monitoring.

- Several years of people management leading data science or ML teams that built products central to the business.

- Strong Python software engineering skills.

- Demonstrated success applying data science to difficult, visible business challenges, including growing a portfolio of models rather than a single one.

- Experience working in a fast-growing, early-stage company.

- A degree in a quantitative or technical field such as mathematics, statistics, computer science, physics or engineering.

- Comfort reporting progress and results to senior stakeholders.

- A stable work history with longer tenures at prior employers.

Bonus points

- Background in fraud, risk or financial services.

- A clear record of career growth.

Benefits

Compensation and benefits

- Base salary: USD 230,000 to 260,000 per year

- Equity

- Health insurance for you and your dependents

- Retirement plan with employer match

- Flexible paid time off

Location and work model

- Remote (US)

- Full-time