Lead a team of data scientists to build customer-facing machine learning products. Design, implement, and deploy production ML models. Partner with engineering, product, and leadership to integrate models into customer experiences.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Title: Data Science Manager
Location: Canada
Compensation: $160,00 – $240,000 CAN (Based on Experience)
About the Role
This is a hands-on data science leadership role where you’ll build new functions from the ground up and own both technical delivery and early organizational design. You’ll focus on customer-facing machine learning products, turning ambiguous business problems into scalable, production-ready ML solutions. The role is based in Canada and collaborates with a distributed team across the Americas. You’ll balance time between coding and architecture, stakeholder management, people leadership, and long-term strategy as the team and scope grow.
Responsibilities
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- Design, implement, and deploy production ML models (e.g., recommendations, predictive systems).
- Hire, mentor, and manage a growing team of data scientists across time zones.
- Own end-to-end ML delivery: problem framing, modeling, deployment, and monitoring.
- Partner with engineering, product, and leadership to integrate models into customer experiences.
- Define data science ways of working, processes, and the long-term roadmap.
Qualifications
- Hands-on data science leader with experience in small to mid-sized, product-focused companies.
- Proven at building or scaling teams while still contributing directly to technical work.
- Comfortable operating in ambiguous, low-structure environments and creating clarity.
- Strong communicator with credibility across technical and non-technical stakeholders.
- Experienced working with remote, distributed teams, ideally including LATAM.
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Required Skills
- Prior experience leading data scientists, including hiring and people management.
- Track record of shipping customer-facing ML products in production (e.g., recommendations, churn, segmentation).
- Strong skills in Python (NumPy, Pandas, scikit-learn) and SQL.
- Experience with cloud ML platforms and big data tools (e.g., AWS/Azure/GCP, Databricks, Spark/Hadoop).
- Exposure to GenAI/LLM concepts (e.g., GPT/BERT, embeddings, vector search) and interest in real-world applications.
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Why Join
- Own and shape a new data science function from day one.
- Build impactful, customer-facing ML products with clear business outcomes.
- Work closely with senior technical and product leaders on strategic initiatives.
- Grow into a broader leadership role as the team and scope expand.
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