Job Title

Data Science Manager Location: Canada | EST Hours Required Salary: $175-220k base + bonus Were partnering with a high-growth product company to hire a Data Science Manager to both ship production ML systems and build a high-performing team. This is a true player-coach role: youll stay hands-on with modeling and system design while setting technical direction, hiring, and mentoring data scientists. The expectation is clear: deliver models that move retention, conversion, and revenue. Youll join a small, autonomous data science team with impact across Product, R&D, Finance, and GTM. The team builds customer-facing data products such as recommendation systems, churn models, and experimentation frameworks that influence how millions of users discover value. Its startup-level ownership with the scale and data of a large, active user base. What Youll Do Design and ship recommendation engines, churn models, and experimentation infrastructure, staying hands-on in code as the team scales Define success metrics, monitor production models, and iterate until business results improve Hire, coach, and develop data scientists; set a high bar for ownership, craft, and impact Partner closely with Product, R&D, Finance, and GTM to identify high-leverage problems and deliver adopted solutions Make pragmatic decisions around tooling, architecture, and methodology, balancing speed with long-term maintainability What Were Looking For 6+ years building and deploying consumer-facing ML systems in production 2+ years leading or managing data scientists or ML engineers Experience building teams, not just operating as an IC Strong Python skills Experience with Databricks or similar ML platforms Comfort across the full ML lifecycle: experimentation, feature engineering, training, deployment, monitoring Proven ability to translate ambiguous business problems into measurable ML outcomes Strong bias toward shipping, iteration, and impact Sound judgment on when to ship an MVP vs. invest in robustness Actively uses AI tools to accelerate development and expects the same from their team Nice to Have Experience with experimentation platforms or causal inference Background in subscription or SaaS businesses Familiarity with TypeScript or production engineering practices