Data Science Manager
Company:Top Hat
Location:Canada
Languages:English
Seniority level:Manager, 6-8 years in data science, ML, or applied statistics; 2-4 years managing data scientists or ML engineers
Experience:6-8 years in data science, ML, or applied statistics; 2-4 years managing data scientists or ML engineers
Skills:
LeadershipPythonSQLArtificial IntelligenceCloud ComputingData AnalysisMachine LearningPyTorchCross-functional Team LeadershipProduct DevelopmentData scienceSparkTensorflowMentoringA/B testing
Requirements:
2-4 years managing data scientists or ML engineers 6-8 years in data science, ML, or applied statistics Expertise in Python, SQL, ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Expertise in modern cloud data platforms (BigQuery, Spark, etc.) Practical experience with LLM-based applications and agent frameworks (Google ADK, LangChain, etc.) Hands-on experience delivering personalization, recommender systems, or predictive analytics in production Strong grasp of causal inference, A/B testing, and evidence-based impact measurement Excellent Communication: Proven skill in presenting technical and non-technical stories to executives, educators, and cross-functional peers.
Responsibilities:
Lead & Develop the Team: Coach, mentor, and grow a team of data scientists. Advance AI-First Capabilities: Contribute to the design of agentic AI, adaptive mastery algorithms, and graph-based knowledge representations. Deliver Impactful Models & Insights: Drive roadmap-aligned projects such as learning mastery diagnostics, recommender systems, and A/B experimentation. Partner Cross-Functionally: Collaborate with Product, Engineering, Learning Materials, and Customer Success. Ensure Quality & Reliability: Establish standards for experimentation, model governance, bias detection, and reproducibility. Tell the Story with Data: Communicate complex technical concepts and evidence-of-impact to leadership and stakeholders.
