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About the role
As a highly motivated and innovative Data Scientist joining our AI/ML team, you will be responsible for driving predictive intelligence for our iPUMPNET smart pumping infrastructure platform. Your role will involve turning high-frequency, multi-sensor data streams into actionable intelligence for condition monitoring, anomaly detection, predictive maintenance, and performance optimization of pumping systems. To succeed in this position, you should have a strong foundation in statistics, machine learning, and software engineering, along with expertise in multivariate time-series analytics, sensor-fusion modeling, and IIoT data engineering. Key Responsibilities: - Design and build multivariate mathematical models that fuse hydraulic, electrical, mechanical, and thermal signals to characterize pump and motor health, operating state, and efficiency in real time. - Create predictive-maintenance, remaining-useful-life (RUL), and anomaly-detection pipelines on high-volume, multi-rate sensor streams, handling missing data, drift, noise, and asynchronous sampling. - Develop fault-detection and root-cause analytics (e.g., cavitation, dry-run, bearing wear, imbalance, misalignment, clogging, electrical faults) using vibration signatures, electrical signatures, and hydraulic behavior. - Build models that detect efficiency degradation and off-BEP operation, and recommend operating set-points that reduce energy consumption and extend asset life. - Validate innovative AI-based ideas and use cases by developing and testing proofs of concept in short cycles, enabling faster business decisions. - Design, prototype, and deliver production-grade AI solutions for use cases across business units and pumping applications. - Architect robust pipelines for ingesting, aligning, cleansing, and feature-engineering large-scale time-series and sensor data, including streaming and batch workflows. - Define the roadmap for in-house AI-powered tools and support the building of AI solutions for diagnostics, reporting, and operator assistance. - Containerize and optimize models for deployment on both cloud and edge/gateway infrastructure close to the pumping assets. - 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 a related field from a tier 1 institute. - Minimum of 8-12 years of professional experience in data engineering, data science, and the development of AI/ML/DL models for deep-tech or industrial products. - 3+ years of formal or informal leadership/mentoring experience. As a highly motivated and innovative Data Scientist joining our AI/ML team, you will be responsible for driving predictive intelligence for our iPUMPNET smart pumping infrastructure platform. Your role will involve turning high-frequency, multi-sensor data streams into actionable intelligence for condition monitoring, anomaly detection, predictive maintenance, and performance optimization of pumping systems. To succeed in this position, you should have a strong foundation in statistics, machine learning, and software engineering, along with expertise in multivariate time-series analytics, sensor-fusion modeling, and IIoT data engineering. Key Responsibilities: - Design and build multivariate mathematical models that fuse hydraulic, electrical, mechanical, and thermal signals to characterize pump and motor health, operating state, and efficiency in real time. - Create predictive-maintenance, remaining-useful-life (RUL), and anomaly-detection pipelines on high-volume, multi-rate sensor streams, handling missing data, drift, noise, and asynchronous sampling. - Develop fault-detection and root-cause analytics (e.g., cavitation, dry-run, bearing wear, imbalance, misalignment, clogging, electrical faults) using vibration signatures, electrical signatures, and hydraulic behavior. - Build models that detect efficiency degradation and off-BEP operation, and recommend operating set-points that reduce energy consumption and extend asset life. - Validate innovative AI-based ideas and use cases by developing and testing proofs of concept in short cycles, enabling faster business decisions. - Design, prototype, and deliver production-grade AI solutions for use cases across business units and pumping applications. - Architect robust pipelines for ingesting, aligning, cleansing, and feature-engineering large-scale time-series and sensor data, including streaming and batch workflows. - Define the roadmap for in-house AI-powered tools and support the building of AI solutions for diagnostics, reporting, and operator assistance. - Containerize and optimize models for deployment on both cloud and edge/gateway infrastructure close to the pumping assets. - Partner with IT, product, and
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