Data Scientist - Predictive Intelligence (Sensor Fusion & Time Series)

Role Overview: You are a highly motivated and innovative Data Scientist joining the AI/ML team to enhance predictive intelligence for the iPUMPNET smart pumping infrastructure platform. Your expertise in statistics, machine learning, and software engineering will be utilized to analyze high-frequency, multi-sensor data streams for condition monitoring, anomaly detection, predictive maintenance, and performance optimization of pumping systems. Key Responsibilities: - Design and build multivariate mathematical models that fuse hydraulic, electrical, mechanical, and thermal signals for real-time characterization of pump and motor health, operating state, and efficiency. - Create predictive-maintenance, remaining-useful-life (RUL), and anomaly-detection pipelines on high-volume, multi-rate sensor streams. - Develop fault-detection and root-cause analytics using vibration signatures, electrical signatures, and hydraulic behavior. - Build models to detect efficiency degradation and off-BEP operation, recommending operating set-points for energy consumption reduction and asset life extension. - Validate AI-based ideas and use cases through proofs of concept development and testing for faster business decisions. - Design, prototype, and deliver production-grade AI solutions for various business units and pumping applications. - Architect robust pipelines for ingesting, aligning, cleansing, and feature-engineering large-scale time-series and sensor data. - Define the roadmap for in-house LLM-powered tools and support the building of Agentic AI solutions. - Containerize and optimize models for deployment on both cloud and edge infrastructure. - Partner with IT, product, and domain teams to launch new AI solutions while adhering to corporate governance guidelines. - Support the building and leading of a high-potential data science and AI team. Qualifications Required: - Bachelors/Master's/PhD degree in Computer Science, Electrical Engineering, Statistics, Physics, Mechanical Engineering, or related field from tier 1 institutes. - Minimum of 8-12 years of professional experience in data engineering, data science, and AI/ML/DL model development. - Strong expertise in multivariate time-series analysis, signal processing, and sensor-fusion techniques. - Hands-on experience with Deep Learning & ML frameworks, Time-series & sequence modeling, Signal processing & feature engineering, and NLP & Generative AI. - Experience deploying solutions using Docker containerization, MLflow/DVC, ONNX, TensorRT, and edge-device optimization. - Problem-solving skills, communication skills, collaborative mindset, and ability to translate technical results into business impact. Company Details (if available): The company offers impactful work where you will contribute to improving the reliability, efficiency, and sustainability of real-world pumping infrastructure. You will have continuous learning opportunities at the intersection of IIoT, sensor fusion, time-series ML, and generative AI while working alongside a talented team passionate about solving challenging problems. Access to cutting-edge technology in AI, machine learning, MLOps, and Agentic AI deployed across cloud and edge platforms adds to the collaborative culture of the company. Role Overview: You are a highly motivated and innovative Data Scientist joining the AI/ML team to enhance predictive intelligence for the iPUMPNET smart pumping infrastructure platform. Your expertise in statistics, machine learning, and software engineering will be utilized to analyze high-frequency, multi-sensor data streams for condition monitoring, anomaly detection, predictive maintenance, and performance optimization of pumping systems. Key Responsibilities: - Design and build multivariate mathematical models that fuse hydraulic, electrical, mechanical, and thermal signals for real-time characterization of pump and motor health, operating state, and efficiency. - Create predictive-maintenance, remaining-useful-life (RUL), and anomaly-detection pipelines on high-volume, multi-rate sensor streams. - Develop fault-detection and root-cause analytics using vibration signatures, electrical signatures, and hydraulic behavior. - Build models to detect efficiency degradation and off-BEP operation, recommending operating set-points for energy consumption reduction and asset life extension. - Validate AI-based ideas and use cases through proofs of concept development and testing for faster business decisions. - Design, prototype, and deliver production-grade AI solutions for various business units and pumping applications. - Architect robust pipelines for ingesting, aligning, cleansing, and feature-engineering large-scale time-series and sensor data. - Define the roadmap for in-house LLM-powered tools and support the building of Agentic AI solutions. - Containerize and optimize models for deployment on both cloud and edge infrastructure. - Partner with IT, product, and domain teams to launch new AI solu