Data Scientist (hybrid)

About Johnson Controls Johnson Controls is a global leader in smart, healthy, and sustainable buildings, serving customers in more than 150 countries. We create intelligent buildings, efficient energy solutions, integrated infrastructure, and next-generation transportation systems. What We Offer Competitive compensation including base salary and performance bonus Comprehensive benefits package (health, dental, vision, retirement) Professional development budget and learning opportunities Work on innovative AI/ML technology at global scale Collaborative culture with growth-oriented mindset Flexible work arrangements and work-life balance What you will do Johnson Controls is seeking a Data Scientist with experience in developing and deploying ML/AI solutions. This role focuses on implementing agentic AI systems, time series analytics, and signal processing capabilities to optimize our building technologies, HVAC systems, and industrial IoT platforms. You'll work alongside senior data scientists while taking ownership of key projects. This is a hybrid position (onsite 3 days per week) based in Glendale, WI. Candidates must be commuting distance, or able to relocate. How you will do it Develop and deploy agentic AI systems that optimize building operations, energy consumption, and equipment performance Build time series forecasting models for energy demand, equipment behavior, and operational patterns Apply signal processing techniques to analyze sensor data and detect anomalies in industrial environments Implement end-to-end machine learning pipelines from data preprocessing through model deployment Contribute to predictive maintenance projects using ML models to forecast equipment failures Collaborate with cross-functional teams to translate business requirements into data science solutions Document methodologies, models, and results for knowledge sharing and reproducibility What you will need Required Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, or related field 4+ years of professional experience developing and deploying ML/AI solutions in industrial, IoT, or similar environments Experience delivering at least 2-3 production ML models with measurable business impact Agentic AI & Machine Learning Hands-on experience building agentic AI systems or autonomous decision-making algorithms Knowledge of reinforcement learning, multi-agent systems, or autonomous optimization frameworks Exposure to LLM-based agents, tool use, or reasoning frameworks for decision-making Solid understanding of supervised and unsupervised ML algorithms with deployment experience Time Series Analysis Experience with time series forecasting using methods like ARIMA, Prophet, LSTM, or similar approaches Hands-on work with seasonal patterns, trend analysis, and time series decomposition Experience applying time series techniques to real-world datasets (sensor data, energy consumption, etc.) Familiarity with handling missing data, outliers, and non-stationary time series Signal Processing Working knowledge of digital signal processing including filtering, FFT, and spectral analysis Experience processing sensor data from industrial equipment (vibration, temperature, pressure, acoustic signals) Ability to implement feature extraction from signal data and apply noise reduction techniques Understanding of frequency domain analysis and pattern detection in signals Strong proficiency in Python with ML libraries (scikit-learn, TensorFlow or PyTorch, XGBoost) Experience with signal processing libraries (scipy.signal, PyWavelets) Working knowledge of time series libraries (statsmodels, Prophet, or tslearn) Experience with at least one cloud platform (Azure preferred, AWS, or GCP) Solid SQL skills and familiarity with data streaming technologies (Kafka, MQTT) Version control with Git and basic MLOps practices Preferred Azure Machine Learning Experience with Azure Machine Learning workspace, automated ML, or deployment capabilities Familiarity with Azure ML pipelines, model registry, or managed endpoints Exposure to Azure Databricks, Azure Synapse Analytics, or Azure IoT Hub Basic knowledge of Azure DevOps for CI/CD or model versioning Genetic AI/Evolutionary Algorithms Exposure to genetic algorithms or evolutionary strategies for optimization problems Experience applying evolutionary computation for hyperparameter tuning or feature selection Interest in nature-inspired algorithms and optimization techniques Predictive Maintenance Experience contributing to predictive maintenance projects or failure prediction models Knowledge of remaining useful life (RUL) estimation or anomaly detection in equipment data Understanding of condition-based monitoring concepts Familiarity with maintenance optimization approaches HIRING SALARY RANGE: $85,000 - $110,000 (Salary to be determined by the education, experience, knowledge, skills, andabilities of the applicant, internal equity, location and alignment with market data.) This position includes acompetitive benefits package. For details, please visit the About Us tab on the Johnson Controls Careers siteat https://jobs.johnsoncontrols.com/about-us