Data Science Manager leading a team of data scientists to drive machine learning initiatives across Resideo's product portfolio. Focusing on real-time insights and scalable data products.
Responsibilities
Lead and mentor a team of data scientists working on multiple product lines (e.g., HVAC diagnostics, water leak detection, and energy optimization).
Drive the development, validation, and deployment of predictive and machine learning models in collaboration with software and data engineering teams.
Promote engineering rigor through structured code reviews, well-maintained Jira boards, and clear project documentation to align data science outputs with business and technical goals.
Partner with product managers to translate ambiguous business questions into measurable, data-driven experiments and insights.
Establish best practices for model lifecycle management, including reproducibility, observability, and ML operations.
Create alignment between data science, data engineering, and analytics organizations to ensure shared data assets and metrics frameworks.
Represent the Data Science function in cross-company strategy discussions and roadmap planning.
Champion continuous learning and development within the team, fostering curiosity and technical excellence.
Requirements
8+ years of combined experience in data science, applied ML, or related technical roles, including at least 3 years in a leadership capacity.
Proven track record of shipping machine learning or predictive analytics solutions in production environments.
Deep experience with Python, SQL, and data science libraries (Scikit-learn, Pandas, TensorFlow/PyTorch, MLFlow).
Familiarity with time-series modeling, anomaly detection, or sensor/IoT data pipelines.
Experience in Databricks, Azure (or AWS) cloud ecosystems, and CI/CD pipelines for ML workloads.
Benefits
Resideo provides comprehensive benefits, including life and health insurance
Duales Studium in Data Science und Künstliche Intelligenz mit Bachelorabschluss (DHBW Mannheim). Fokus auf Digitalisierung, Prozessoptimierung und KI - gestützte Modelle.
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