Senior Data Scientist at Johnson Controls deploying AI/ML solutions to optimize building technologies and industrial IoT platforms. Collaborating with teams and mentoring junior data scientists in a hybrid work environment.
Responsibilities
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
Requirements
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
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
Experience with time series forecasting using methods like ARIMA, Prophet, LSTM, or similar approaches
Familiarity with handling missing data, outliers, and non-stationary time series
Working knowledge of digital signal processing including filtering, FFT, and spectral analysis
Experience processing sensor data from industrial equipment (vibration, temperature, pressure, acoustic signals)
Strong proficiency in Python with ML libraries (scikit-learn, TensorFlow or PyTorch, XGBoost)
Experience with at least one cloud platform (Azure preferred, AWS, or GCP)
Benefits
Competitive compensation including base salary and performance bonus
Senior Pricing Data Scientist optimizing pricing strategy at Sabadell Zurich. Leading GLM model development and collaborating with Product and Claims teams.
Data Scientist Intern at PG&E developing system performance monitoring tools using operational datasets. Collaborating with the System Performance Monitoring team to support grid modernization technologies.
Clinical Data Manager responsible for overseeing end - to - end data management study activities at GSK. Ensuring quality and compliance in key deliverables for clinical trials.
Senior Data Scientist improving airport operations by creating passenger forecasts and resource needs. Collaborating within a multidisciplinary team in Denmark's biggest airport.
Staff Data Scientist developing AI - driven solutions for women's health leveraging data and analytics. Collaborating with interdisciplinary teams to enhance radiologic procedures with advanced technologies.
Senior Data Scientist forecasting weather - driven incidents and staffing needs at Gridware, enhancing grid management operations through advanced analytics.
ML Engineer building configurable ML systems that drive enterprise growth outcomes. Working closely with high - level stakeholders to translate business challenges into ML solutions.
Senior Data Scientist advancing Cotality's geocoding product. Collaborating with a cross - functional team to enhance address standardization and geocoding services.
Data Manager leading the Quality Assurance Data Analysis team at Florida Department of Children and Families. Responsible for performance measures, executive presentations, and continuous improvement plans.
Data Scientist / Engineer developing and implementing AI solutions for insurance clients. Contributing to fraud detection and automation in a hybrid work environment.