Head of Data Science, Analytics

Role Overview

• Build and own the company’s data science and analytics function from the ground up.
• Partner with executive leadership, product, live operations, marketing, finance, and technology teams to turn business questions into clear insights, recommendations, and action plans.
• Develop the core analytics roadmap across player behavior, retention, engagement, monetization, game health, content performance, live operations, user segmentation, forecasting, and business performance.
• Personally perform hands-on analysis, including SQL querying, dashboarding, data modeling, KPI development, reporting, statistical analysis, and business case development.
• Improve the quality, consistency, and reliability of company metrics, reporting, and data definitions.
• Identify gaps in data collection, instrumentation, data architecture, reporting, and operational visibility.
• Partner with engineering and data stakeholders to improve data pipelines, data quality, data governance, and access to trusted datasets.
• Design dashboards and executive reporting that help leaders understand what is happening, why it is happening, and what should be done next.
• Lead analysis on player lifecycle, cohort behavior, monetization trends, feature performance, content performance, game economy, and live-service operations.
• Support experimentation, A/B testing, measurement frameworks, and decision-ready analysis for product and business initiatives.
• Implement practical AI-driven solutions to accelerate analytics workflows, automate repetitive reporting, improve insight generation, and support better business decisions.
• Explore and deploy AI agents, copilots, workflow automations, and other tools that improve productivity across analytics, operations, product, and leadership reporting.
• Establish best practices for responsible AI use, data privacy, analytical rigor, documentation, and repeatable workflows.
• Over time, hire, coach, and lead a high-performing data science, analytics, and/or BI team.

Requirements

• 8+ years of experience in data science, analytics, business intelligence, product analytics, or a related data discipline.
• Experience operating in a gaming, digital product, SaaS, consumer technology, marketplace, or live-service environment.
• Strong hands-on analytical skills, including advanced SQL and experience with Python, R, or similar analytical tools.
• Proven ability to translate ambiguous business problems into structured analysis, clear recommendations, and executive-level narratives.
• Experience building dashboards, reports, KPI frameworks, and decision-support tools for senior leadership.
• Strong understanding of product analytics, user behavior, retention, engagement, monetization, segmentation, cohort analysis, forecasting, and experimentation.
• Experience working with data engineering, product, finance, marketing, and executive teams.
• Experience implementing or adopting AI tools, GenAI, copilots, agentic workflows, workflow automation, or AI-enabled analytics processes.
• Ability to operate independently in a hands-on capacity before a larger team is built.
• Strong communication skills, with the ability to explain complex analysis in clear business language.
• Demonstrated ability to build structure in an environment where data, processes, tooling, or reporting may still be maturing.

Tech Stack

• Python
• SQL

Benefits

• Comprehensive benefits package (health, dental, and vision) including HSA/WSA spending account from Day 1
• Participation in the Employee Stock Option Plan (ESOP)
• RRSP participation and matching
• 15 Vacation Days + 10 Wellness Days