Job Description

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, 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: $115,000 - $155,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, location and alignment with market data.) This position includes a competitive benefits package. For details, please visit the About Us tab on the Johnson Controls Careers site at https://jobs.johnsoncontrols.com/about-us

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