Head of Data Science, Tapestry

Software Engineering Mountain View, CA (HQ), San Francisco, CA

About Tapestry

Tapestry is Alphabet’s moonshot for the electric grid, working at the frontier where energy’s complexity meets AI’s potential. We were born at X, the innovation lab responsible for breakthrough technologies like Waymo, Verily and Google Brain.

To keep pace with humanity’s growing energy needs, the world needs a grid that is visible and understandable. We provide that clarity by building advanced, AI-enabled analytical and planning tools that allow the entire energy ecosystem to plan smarter, move faster, and operate more efficiently—ensuring electricity remains reliable and affordable for everyone.

Joining Tapestry allows you to do the best work of your life as part of a multidisciplinary team of experts in AI, energy systems, software engineering and product design—all collaborating to reshape energy on a global scale. If you want to tackle problems that matter and build tools with real impact, we would love to meet you. Learn more about our team and our mission here .

About the role:

At Tapestry, data powers everything we build. As Head of Data Science, you will lead a world-class team bridging complex business strategy and advanced technical execution. Partnering closely with ML experts, you will define key metrics, design scalable data curation pipelines, and drive high-impact experimentation to translate model insights into tangible value that transforms electric grid visibility and resilience.

How you will contribute…

• Team Leadership & Strategic Delivery
• People Management: Recruit, mentor, and lead a world-class data science team, fostering talent through active mentorship and clear career paths.
• Cross-Functional Alignment: Translate high-level business goals into rigorous data science roadmaps in partnership with engineering, product, and power system experts.
• Executive Communication: Persuasively communicate strategic recommendations and long-term business impact to senior leaders.
• Data Integrity & Curation Strategy
• Pipeline Oversight: Guide the discovery, investigation, and analysis of large, complex datasets to support scalable machine learning.
• Business Metrics: Define core metrics and experimental designs that translate ML model performance into business value.
• Quality Control & Annotation: Establish frameworks for data integrity across multi-stage ML processes and drive statistical rigor in data annotation.
• Problem Definition & Advanced Analytics
• Grid Visibility: Explore new problem spaces to enhance electric grid resilience.
• Experimentation: Standardize A/B testing and experimental frameworks to validate hypotheses and measure product impact.
• Best Practices: Champion modern data science workflows, including GenAI techniques for analysis and synthesis.

What you should have…

• PhD or Master’s in a quantitative field with 10+ years of industry experience as a statistician, quantitative analyst, or data scientist.
• Proficiency in Python, SQL, R, Pandas, Scikit-Learn, and related ML frameworks.
• 8+ years managing high-performing data science teams, delivering production-grade solutions.
• Track record of identifying where data science adds value during early product development and influencing cross-functional collaboration.
• Advanced experimental design skills (A/B testing, multivariate analysis, stochastic models, and sampling methods) to address bias, variance, and data drift.
• Experience building tooling to analyze large, heterogeneous datasets.
• Ability to balance high-level product strategy ("zoom out") with technical unblocking ("zoom in").
• Strong collaboration with ML and software engineering teams to ship production-ready systems.
• Exceptional storytelling skills, translating complex pipelines and metrics into clear business value.

Would be great to have…

• Thrives in ambiguity, setting goals and delivering in fast-changing environments.
• Fast learner adaptable to diverse technologies and industries.
• Experience delivering scalable enterprise solutions in startup or high-growth environments.
• Experience with electric power grid data and utility networks, bridging the gap between power systems and machine learning.

Tapestry Values

• Take charge: We take initiative and own outcomes that move the mission forward.
• Transform with purpose: We build solutions that solve real problems and create meaningful impact.
• Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
• Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
• Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer:

• Competitive salary and equity
• Medical, dental, and vision coverage
• Generous PTO and flexible hybrid work model
• 401(k) with employer contribution
• The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $207,000 - $330,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.

An Equal Opportunity Workplace

At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.