Head of Applied Science / Data Science
San Francisco, CA (Hybrid)
- Pay
$320,000–380,000/year · Base — pay source
For US based applicants: The US base salary range for this full-time position is $320,000 - $380,000 annually + equity + benefits Our salary ranges are determined by role, level and location
Read the full posting- Work setting
Hybrid — work setting source
Listed location: San Francisco, CA (Hybrid)
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full Time
From the employer’s posting
What you’ll work on
Full postingOur Applied Science / Data Science team is a world-class organization focused on using data, experimentation, machine learning, and AI to shape product strategy and accelerate business growth.
This will be a leadership role overseeing our applied science / data science team and you will lead a team of high-performing data scientists responsible for solving some of the company’s most strategic product and business challenges.
Lead, mentor, and grow a team of applied and data scientists
Define and execute the applied data science roadmap with Product and Engineering
Drive statistical, machine learning, and experimentation work to improve product performance
Partner with engineers to deploy production-ready models
Present insights and recommendations to senior and executive leaders
From the employer’s posting
Our Applied Science / Data Science team is a world-class organization focused on using data, experimentation, machine learning, and AI to shape product strategy and accelerate business growth. We partner closely with Product, Engineering, Marketing, Sales, and Customer Success to build intelligent products, optimize customer experiences, and drive measurable business impact.
This will be a leadership role overseeing our applied science / data science team and you will lead a team of high-performing data scientists responsible for solving some of the company’s most strategic product and business challenges. You will define the vision for applied data science across multiple product areas, develop innovative analytical and machine learning solutions, and partner with senior leaders to influence company strategy. This is a highly visible leadership role that blends people management, technical excellence, and cross-functional influence.
Lead, mentor, and grow a team of Applied Scientists / Data Scientists
Define and execute the applied data science roadmap in partnership with Product, Engineering, and executive stakeholders
Drive the development of statistical models, machine learning solutions, experimentation frameworks, and causal inference methodologies
Partner closely with engineering teams to operationalize models and deploy production-ready solutions
Present insights and recommendations to senior leadership and executive stakeholders
Education & alternatives
Your Expertise - Master’s or Ph.D. in Statistics, Computer Science, Economics, Operations Research, Mathematics, Machine Learning, or a related quantitative field; Bachelor’s degree with equivalent industry experience also considered - 8+ years of experience in Data Science, Machine Learning, Analytics, or related disciplines
Tools in this posting
- Python
- SQL
Source — Tool mentions in context
- Experience partnering closely with Product and Engineering organizations to deliver data-driven product improvements - Strong proficiency in Python and SQL with experience working on large-scale datasets - Excellent communication skills with the ability to influence executive stakeholders through data-driven storytelling
Posting record
Report an errorOpen 3 monthsWe first saw this posting 113 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 9, 2026 · 113 days ago
- Recorded sightings
- 67
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
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Job description
About the Role
Our Applied Science / Data Science team is a world-class organization focused on using data, experimentation, machine learning, and AI to shape product strategy and accelerate business growth. We partner closely with Product, Engineering, Marketing, Sales, and Customer Success to build intelligent products, optimize customer experiences, and drive measurable business impact.
This will be a leadership role overseeing our applied science / data science team and you will lead a team of high-performing data scientists responsible for solving some of the company’s most strategic product and business challenges. You will define the vision for applied data science across multiple product areas, develop innovative analytical and machine learning solutions, and partner with senior leaders to influence company strategy. This is a highly visible leadership role that blends people management, technical excellence, and cross-functional influence.
What You’ll Accomplish
- Lead, mentor, and grow a team of Applied Scientists / Data Scientists, fostering technical excellence and career development
- Define and execute the applied data science roadmap in partnership with Product, Engineering, and executive stakeholders
- Drive the development of statistical models, machine learning solutions, experimentation frameworks, and causal inference methodologies to improve product performance and customer outcomes
- Establish best practices for experimentation, measurement, forecasting, and decision-making across the organization
- Translate ambiguous business problems into scalable analytical and machine learning solutions
- Influence product strategy by identifying opportunities through deep analysis of customer behavior, experimentation, and business performance
- Partner closely with engineering teams to operationalize models and deploy production-ready solutions
- Present insights and recommendations to senior leadership and executive stakeholders to influence strategic decisions
- Build a culture of scientific rigor, operational excellence, and continuous innovation across the data science organization
Your Expertise
- Master’s or Ph.D. in Statistics, Computer Science, Economics, Operations Research, Mathematics, Machine Learning, or a related quantitative field; Bachelor’s degree with equivalent industry experience also considered
- 8+ years of experience in Data Science, Machine Learning, Analytics, or related disciplines
- 3+ years of experience managing and developing high-performing data science teams
- Deep expertise in experimentation, causal inference, statistical modeling, predictive modeling, and machine learning
- Experience partnering closely with Product and Engineering organizations to deliver data-driven product improvements
- Strong proficiency in Python and SQL with experience working on large-scale datasets
- Excellent communication skills with the ability to influence executive stakeholders through data-driven storytelling
- Demonstrated success leading cross-functional initiatives from ideation through production
You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.
For US based applicants:
- The US base salary range for this full-time position is $320,000 - $380,000 annually + equity + benefits
- Our salary ranges are determined by role, level and location
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Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
For US based applicants: The US base salary range for this full-time position is $320,000 - $380,000 annually + equity + benefits Our salary ranges are determined by role, level and location
- Location & working pattern
San Francisco, CA (Hybrid)
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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