Head of Data Science, Tapestry at X, the moonshot factory in Mountain View, CA (HQ), San Francisco, CA

Job description

• 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.

Responsibilities

• 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.

Requirements

• 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.
• 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.

Skills

Required

• Exceptional storytelling skills.

Preferred

• Thrives in ambiguity.

Benefits

• A culture that supports growth, ownership, and meaningful impact, along with…
• Competitive salary and equity
• Medical, dental, and vision coverage
• Generous PTO and flexible hybrid work model
• 401(k) with employer contribution
• Professional development
• 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.