• Organize and evolve the Pix squads' workflow • Support the structuring of initiatives and ensure their execution with quality and predictability • Work closely with Engineering, Design, and Data teams • Organize and maintain a structured, up-to-date backlog, ensuring clarity and prioritization of initiatives • Assist in writing user stories, documentation, and defining flows • Ensure initiatives are ready for development • Monitor progress of tasks and deliverables • Identify and flag blockers, dependencies, and gaps • Support alignment between Product, Engineering, and stakeholders • Ensure visibility of the workflow • Run the squad's operational rituals • Drive continuous improvement of the development flow

• 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.

• Partner with Client Support and Styling stakeholders, providing the analytical and technical expertise needed to turn data into actionable business strategy. • Design, execute, and analyze experiments and observational studies that uncover key insights for the company. • Provide training and guidance on self-service tools and platforms, ensuring partners can confidently navigate dashboards and reports.

• Collaborate closely with the Snowflake engineering team to define, spec, and validate data requirements for models and AI applications • Serve as the translation layer between data engineering and AI/ML teams, ensuring data is structured, clean, and optimized for downstream use • Enable and support agentic AI workflows by designing and maintaining the data layers that power agent memory, context retrieval, and tool-use • Build and maintain data models and transformation logic on top of Snowflake to support predictive and generative AI use cases • Identify and resolve data quality issues in collaboration with the engineering team • Partner with marketing science and analytics teams to ensure data assets are accessible and model-ready • Automate and streamline data validation processes to improve reliability of AI-facing data pipelines