We are seeking a seasoned Lead Data Scientist to spearhead data-driven innovation in the industrial and buildings domain. This role involves leading a team to develop advanced analytics and machine learning solutions that optimize building operations, enhance energy efficiency, and enable predictive maintenance across industrial assets and smart infrastructure. **Strategic Leadership** - Define and execute the data science strategy for smart buildings and industrial systems. - Collaborate with engineering, product, and operations teams to align analytics initiatives with business and sustainability goals. - Drive adoption of AI/ML solutions across building automation, HVAC systems, energy management, and asset monitoring. **Advanced Analytics & Modeling** - Develop predictive models for equipment failure, energy consumption forecasting, and occupant behavior analysis. - Apply time-series analysis, anomaly detection, and optimization algorithms to real-time sensor and IoT data. - Leverage geospatial and environmental data to improve building performance and safety. **Project & Team Management** - Lead cross-functional data science projects from ideation to deployment. - Mentor junior data scientists and foster a culture of experimentation and continuous improvement. - Ensure robust model validation, documentation, and compliance with industry standards. **Stakeholder Engagement** - Translate complex analytical insights into actionable recommendations for facility managers, engineers, and business leaders. - Build intuitive dashboards and visualizations to monitor KPIs like energy usage, equipment health, and operational efficiency. **Machine Learning & AI** - Supervised and unsupervised learning - Deep learning (CNNs, RNNs, transformers) - Reinforcement learning for control systems **Statistical Analysis & Modeling** - Regression, classification, clustering - Time-series forecasting and anomaly detection - Bayesian inference and probabilistic modeling **Programming & Tools** - Python, R, SQL - Libraries: scikit-learn, TensorFlow, PyTorch, XGBoost, Statsmodels - Data manipulation: Pandas, NumPy, Dask **Big Data & Cloud Platforms** - Spark, Hadoop, Kafka - AWS, Azure, GCP (especially IoT and analytics services) **Data Visualization & BI** - Dash, Plotly, Matplotlib, Seaborn - Power BI, Tableau, Grafana **MLOps & Deployment** - Model versioning, CI/CD pipelines - Docker, Kubernetes, MLflow - Integration with BMS and industrial control systems **Domain-Specific Expertise** - Sensor fusion and IoT analytics - Building automation protocols (BACnet, Modbus) - Energy modeling and sustainability metrics - Master’s or Ph.D. in Data Science, Engineering, Statistics, or a related field. - 7+ years of experience in data science, with at least 2 years in a leadership role. - Proven experience in industrial or smart building environments. - Strong communication and stakeholder management skills. Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable. Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.