Director, People Data Science

Role Summary

Our mission at HubSpot is to help millions of organizations grow better. The People Analytics team helps HubSpotters do the best work of their careers by building a deep, data-driven understanding of what makes HubSpot a great place to work—and continuously improving it.

As Director of People Data Science, you’ll lead the technical strategy behind how we use data and AI to inform decisions across the People Team. You’ll guide a high-performing team across data science, analytics engineering, and data products, ensuring your work drives measurable impact for every HubSpotter. This is a leadership role with both strategic ownership and technical depth, shaping the future of people analytics at scale.

What You’ll Do

• Define and own the People Analytics Team’s data science and analytics engineering strategy, setting a clear roadmap aligned to People Team priorities.
• Lead and develop a high-performing team of data scientists, fostering a culture of innovation, growth, and impact.
• Build scalable, product-oriented data solutions, including models, tools, and frameworks that are widely adopted and drive decision-making.
• Partner with HR leaders and cross-functional stakeholders to translate business challenges into high-impact data and AI solutions.
• Oversee development of predictive models that forecast people outcomes, identify risks, and enable proactive decision-making.
• Drive the creation of AI-powered tools and data products that deliver insights to managers and leaders at scale.
• Ensure the integrity, governance, and scalability of data infrastructure supporting People Analytics.
• Lead complex, high-stakes analytical initiatives and communicate insights clearly to non-technical audiences to influence decisions.
• Shape HubSpot’s approach to AI within the People Team, including build vs. buy decisions and cross-team collaboration.
• Ensure ethical, compliant, and responsible use of employee data across all initiatives.
  
  

What You’ll Bring

Required Qualifications

• 8–10+ years of experience in data science, analytics, or a related field, including 5+ years leading technical teams.
• Deep technical expertise in data science, including experience building and deploying models and working across the data stack.
• Proven experience leading multidisciplinary teams (e.g., data science and analytics engineering).
• Strong track record of delivering scalable data products or solutions that drive measurable business impact.
• Ability to translate complex technical work into clear insights that influence non-technical stakeholders.
• Experience partnering cross-functionally in matrixed environments and influencing senior stakeholders.
• Strong leadership skills with a focus on developing talent and building inclusive, high-performing teams.
• Understanding of ethical considerations and best practices when working with people or employee data.

Nice-to-Have Qualifications

• Experience working with HR or people data (e.g., HRIS, engagement surveys, behavioral data).
• Familiarity with AI applications such as large language models, AI agents, or applied AI in product or research contexts.
• Experience building or scaling data products within a People, HR, or internal analytics function.
• Background in analytics engineering, data infrastructure, or data product development.