Head of Data Science, Tapestry

Tapestry

$207K — $330K *
Energy & Utilities
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • PhD or Master's in quantitative field with 10+ years industry experience as statistician, analyst, or data scientist.
  • Proficiency in Python, SQL, R, Pandas, Scikit-Learn, and related ML frameworks.
  • 8+ years leading high-performing data science teams in delivering production-grade solutions.
  • Demonstrated capability in identifying data science value during product development and facilitating cross-functional collaboration.
  • Advanced skills in experimental design addressing bias, variance, and data drift.

Responsibilities

  • Lead and mentor a high-caliber data science team, nurturing talent and career paths.
  • Translate business goals into actionable data science strategies in collaboration with engineering and product teams.
  • Effectively communicate strategic insights to senior leadership for business impact.
  • Oversee the analysis of complex datasets to support scalable machine learning initiatives.
  • Define business metrics and experimental designs to quantify model performance.
  • Establish data integrity frameworks across ML processes and ensure statistical rigor in data annotation.
  • Explore new avenues to enhance electric grid resilience through advanced analytics.

Benefits

  • Competitive salary and equity options.
  • Comprehensive medical, dental, and vision coverage.
  • Generous paid time off and a flexible hybrid work environment.
  • 401(k) with employer contributions.
  • Opportunities for professional development.
  • Work on significant real-world problems with support from Alphabet.
Full Job Description
H e a d o f D a t a S c i e n c e , T a p e s t r y

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

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...
  1. 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.
  1. 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.
  1. 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:

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.

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