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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