Data Scientist for Product Sustainability at Roche managing environmental data for sustainability reporting. Bridging Global Sustainability Experts and IT systems to ensure actionable insights for product emissions and compliance.
About the role
- 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
- 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
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