Job Description

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.