Data Scientist developing and deploying ML/AI solutions for optimizing building operations and industrial IoT platforms. Collaborating with senior data scientists in a hybrid working environment.
Responsibilities
Develop and deploy agentic AI systems that optimize building operations, energy consumption, and equipment performance
Build time series forecasting models for energy demand, equipment behavior, and operational patterns
Apply signal processing techniques to analyze sensor data and detect anomalies in industrial environments
Implement end-to-end machine learning pipelines from data preprocessing through model deployment
Contribute to predictive maintenance projects using ML models to forecast equipment failures
Collaborate with cross-functional teams to translate business requirements into data science solutions
Requirements
Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, or related field
4+ 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
Working knowledge of digital signal processing including filtering, FFT, and spectral analysis
Strong proficiency in Python with ML libraries (scikit-learn, TensorFlow or PyTorch, XGBoost)
Benefits
Competitive compensation including base salary and performance bonus
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