Lead Decision Scientist (Web)

About the role

The role involves shaping critical business decisions through advanced analytics, experimentation, and data-driven strategy. You will partner with product, marketing, engineering, and finance teams to uncover insights that influence roadmaps, investments, and growth initiatives.

Responsibilities

• Act as a strategic analytics partner, owning the decision-making framework for web experiences and helping cross-functional teams understand customer behavior, optimize performance, and identify growth opportunities.
• Partner with product, marketing, engineering, and finance teams to define analytics strategies, prioritize opportunities, and influence business decisions through data.
• Build and communicate analytical narratives that transform complex findings into clear recommendations and actionable strategies for leadership and operational teams.
• Analyze the complete digital customer journey, identifying conversion opportunities, user behavior trends, funnel improvements, and areas for optimization.
• Design and evaluate experiments, including A/B testing and multivariate testing, using statistical methods and causal inference techniques to measure impact.
• Develop measurement frameworks and key performance indicators that align user behavior insights with business objectives.
• Collaborate with engineering teams to improve event tracking, data pipelines, and analytics infrastructure supporting digital performance measurement.
• Integrate data from platforms such as Google Analytics, BigQuery, and Databricks to support reporting, experimentation, and decision-making.
• Develop scalable self-service analytics solutions and reporting frameworks using industry best practices.
• Use AI-powered tools and automation workflows to accelerate analysis, improve productivity, and help shape modern analytics practices.
• Investigate consumer behavior across segments and markets to uncover trends that inform product, marketing, and revenue strategies.

Requirements

• Strong analytical expertise, business judgment, and the ability to influence teams through data-driven insights.
• Comfortable working in ambiguous environments, asking the right questions, and connecting technical analysis with strategic outcomes.
• 6+ years of experience in analytics, data science, decision science, or a related field within a consumer-focused technology environment.
• Bachelor’s degree or higher in a quantitative discipline such as economics, statistics, mathematics, operations research, or equivalent practical experience.
• Proven ability to influence product and business strategy through data analysis and measurable recommendations.
• Advanced proficiency in SQL and Python or R for statistical analysis and data exploration.
• Hands-on experience with experimentation platforms and optimization programs.
• Strong knowledge of web analytics platforms such as Google Analytics 4 (GA4) and/or Adobe Analytics.
• Experience collaborating with data engineering teams to build and maintain event tracking and centralized data environments.
• Ability to communicate complex analytical concepts clearly to technical and non-technical stakeholders.
• Experience using AI-assisted development and analytics tools to improve workflows and increase productivity.
• Strong problem-solving mindset, ownership mentality, curiosity, and ability to independently identify opportunities.
• Experience with subscription, e-commerce, or freemium business models is a plus.
• Familiarity with tools such as Google Tag Manager, Tealium, dbt, revenue forecasting frameworks, LTV modeling, incrementality testing, or marketing mix modeling is preferred.

Benefits

• Competitive compensation package: United States: $133,000 - $195,000 USD base salary range. Canada: $147,500 - $173,000 CAD base salary range.
• Equity opportunities as part of the overall compensation package.
• Comprehensive medical, dental, vision, life, and disability insurance plans.
• Employer-supported retirement programs, including 401(k) matching in the US and RRSP/DPSP options in Canada.
• Flexible paid time off and company-wide scheduled days off throughout the year.
• Winter and summer company shutdown periods to support work-life balance.
• Employee Assistance Program focused on mental wellness and personal support.
• Learning and development programs to support career growth.
• Remote work support, including equipment, tools, and reimbursement resources.
• Remote-first working environment with flexibility across eligible locations.
• Access to premium membership benefits and company products.