Senior Data Scientist; hybrid

Position: Senior Data Scientist (hybrid)
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** 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 Senior Data Scientist with a strong practical background in deploying production-ready AI/ML solutions. This role focuses on developing advanced agentic AI systems, time series analytics, and signal processing capabilities to optimize our building technologies, HVAC systems, and industrial IoT platforms. 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
*** Design and deploy agentic AI systems that autonomously optimize building operations, energy consumption, and equipment performance
* Develop and implement advanced time series forecasting models for energy demand, equipment behavior, and operational patterns
* Apply signal processing techniques to analyze sensor data, detect anomalies, and extract meaningful patterns from noisy industrial environments
* Build end-to-end machine learning pipelines from data ingestion through model deployment and monitoring in production systems
* Lead predictive maintenance initiatives using ML models to forecast equipment failures and optimize maintenance schedules
* Collaborate with engineering and operations teams to translate business problems into practical data science solutions
* Mentor junior data scientists and establish best practices for model development and deployment
** What you will need  Required
*** Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, or related field
* 7+ 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, Tensor Flow or PyTorch, XGBoost)
* Experience with signal processing libraries (scipy.signal, PyWavelets)
* Working knowledge of time series libraries (stats models, 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…