Role Overview:

As a Data Scientist at our company, you will be a part of the AI/ML team 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. You will be expected to 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. Success in this role will require a passion for working with real-world sensor data and the ability to communicate results effectively to technical and business stakeholders.

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, handling missing data, drift, noise, and asynchronous sampling.
• Develop fault-detection and root-cause analytics using vibration signatures, electrical signatures, and hydraulic behavior for condition monitoring and diagnostics.
• Build models to detect efficiency degradation and recommend operating set-points that reduce energy consumption and extend asset life for performance and energy optimization.
• Validate AI-based ideas and use cases by developing and testing proofs of concept in short cycles for POC development.
• Design, prototype, and deliver production-grade AI solutions for various business units and pumping applications for end-to-end AI development.
• Architect robust pipelines for ingesting, aligning, cleansing, and feature-engineering large-scale time-series and sensor data, including streaming and batch workflows for data engineering.
• Define the roadmap for in-house LLM-powered tools and support the building of Agentic AI solutions for diagnostics, reporting, and operator assistance for generative AI.
• Containerize and optimize models for deployment on both cloud and edge/gateway infrastructure for MLOps (Cloud & Edge).
• Partner with IT, product, and domain teams to launch new AI solutions while adhering to corporate governance guidelines for collaboration and governance.
• Support the building and leading of a high-potential data science and AI team for mentoring and team building.

Qualifications Required:

• Bachelors/Master's/PhD degree in Computer Science, Electrical Engineering, Statistics, Physics, Mechanical Engineering, or a related field from a reputed institute.
• Minimum of 8-12 years of professional experience in data engineering, data science, and the development of AI/ML/DL models.
• Strong expertise in multivariate time-series analysis, signal processing, and sensor-fusion techniques.
• Hands-on experience with Deep Learning & ML frameworks, time-series modeling, signal processing, and NLP & Generative AI.
• Exposure to deploying solutions to production using Docker containerization, MLflow/DVC, ONNX, TensorRT, and edge-device optimization.
• Problem-solving and communication skills, collaborative mindset, and ability to translate technical results into business impact.

(Note: Additional details about the company were not mentioned in the provided job description.) Role Overview:

As a Data Scientist at our company, you will be a part of the AI/ML team 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. You will be expected to 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. Success in this role will require a passion for working with real-world sensor data and the ability to communicate results effectively to technical and business stakeholders.

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, handling missing data, drift, noise, and asynchronous sampling.
• Develop fault-detection and root-cause analytics using vibration signatures, electrical signatures, and hydraulic behavior for condition monitoring and diagnostics.
• Build models to detect efficiency degradation and recommend operating set-