Senior Director, Analytics and Data Science

About the opportunity

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Director, Analytics and Data Science, Core Product & Growth based in Canada . This is a senior leadership opportunity to shape how analytics and data science drive product and growth strategy at a large-scale consumer technology organization. You will lead decision science and data science focused on understanding acquisition, activation, engagement, retention, and user growth. The role combines strategic leadership with hands-on involvement in analytical methods, experimentation, forecasting, and AI-native ways of working. You will build scalable standards and operating practices that move analytics from reactive support to proactive strategic partnership. Working closely with Product, Engineering, Marketing, Data Engineering, and fellow analytics leaders, you will influence roadmaps and investment decisions. You will also develop a high-performing team and raise the quality and impact of its analytical work. This is an ideal environment for a data leader who thrives on ambiguity, behavioral insights, innovation, and measurable business impact. Accountabilities: Lead and develop decision scientists and data scientists, establishing a high quality bar while coaching team members toward greater technical expertise, strategic thinking, and leadership. Own the models and forecasts used to understand and predict monthly active user growth, including the key drivers behind acquisition, activation, engagement, retention, and churn. Lead exploratory and strategic analytics that identify opportunities to grow the user base and translate behavioral insights into actionable product and business priorities. Establish consistent standards for how analytical work is scoped, conducted, reviewed, communicated, and documented, ensuring quality and rigor across the team. Partner with Revenue Analytics and Data Engineering leadership to define common metrics, experimentation standards, and shared operating practices. Build an operating model that enables the analytics and data science organization to engage earlier in product and engineering roadmaps, influencing what should be built, measured, and tested. Apply AI-native approaches to analytical work, including coding agents, automated analysis, and intelligent tooling, while defining which activities should be automated and where human judgment remains essential. Bring strong inferential and causal thinking to product and growth questions, helping teams understand not only what users do but why they behave the way they do. Provide senior leadership with clear, evidence-based recommendations and determine which analytical questions deserve investment and which should not be pursued. Collaborate across a data-rich consumer technology environment involving billions of behavioral and location-related events, subscription activity, connected devices, and complex network effects. Requirements: 10+ years of experience in analytics, data science, decision science, or a closely related discipline, including at least 5 years in people management at a senior leadership level. Deep expertise in inferential and causal analytics, with the ability to lead and effectively challenge machine learning practitioners. Strong knowledge of engagement, retention, churn, cohort analysis, and other metrics used to understand consumer behavior and growth. Proven experience forecasting a company-level business metric and being accountable for the resulting outcomes. Strong technical proficiency with SQL and Python or R, combined with the ability to work confidently with modern data and analytics platforms. Experience with Databricks, experimentation platforms such as Statsig, Tableau or comparable BI tools, and AI-native analytics tools such as Hex or AI/BI. Hands-on experience using coding agents such as Claude Code or equivalent tools in analytical workflows, with a demonstrated willingness to work AI-first. Bachelor's degree or equivalent practical experience required; a master's degree or PhD in social science, psychology, behavioral science, or a related field is a plus. Demonstrated success transforming analytics teams from reactive request fulfillment into embedded, proactive strategic partners. Strong people-development skills, including a track record of growing analysts and data scientists into senior contributors and leaders. Experience establishing analytical standards, operating models, experimentation practices, and quality frameworks that teams consistently adopt. Strong curiosity about human behavior and the ability to formulate hypotheses rather than simply respond to data requests. Excellent executive communication, prioritization, influencing, and stakeholder-management skills, with the judgment to determine where the team should focus its resources. Experience working with product and engineering teams in an embedded model and familiarity with B2C subscription businesses is highly desirable. Familiarity with experimentation involving network effects is a plus. Benefits: US base salary range of $247,000–$366,000 USD, with final compensation determined by factors including location, experience, skills, and background. Comprehensive medical, dental, vision, life, and disability insurance, with plans fully paid for US employees. Equity as part of the overall compensation package. 401(k) plan with company matching. Paid parental leave. Mental Wellness Program and Employee Assistance Program. Flexible paid time off, company holidays, and summer and winter shutdown periods. Learning and development programs supporting ongoing professional growth. Equipment, tools, and reimbursement support for a productive remote working environment. Free premium membership and connected tracking devices as employee perks. Remote-first working environment, allowing employees to work remotely within the US and Canada unless otherwise specified. Mission-driven culture centered on integrity, direct communication, customer focus, and high-impact execution. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Qualifications

• : 10+ years of experience in analytics, data science, decision science, or a closely related discipline, including at least 5 years in people management at a senior leadership level.
• Deep expertise in inferential and causal analytics, with the ability to lead and effectively challenge machine learning practitioners.
• Strong knowledge of engagement, retention, churn, cohort analysis, and other metrics used to understand consumer behavior and growth.
• Proven experience forecasting a company-level business metric and being accountable for the resulting outcomes.
• Strong technical proficiency with SQL and Python or R, combined with the ability to work confidently with modern data and analytics platforms.
• Experience with Databricks, experimentation platforms such as Statsig, Tableau or comparable BI tools, and AI-native analytics tools such as Hex or AI/BI.
• Hands-on experience using coding agents such as Claude Code or equivalent tools in analytical workflows, with a demonstrated willingness to work AI-first.
• Bachelor's degree or equivalent practical experience required; a master's degree or PhD in social science, psychology, behavioral science, or a related field is a plus.