Padmi

Sr. Principal Engineer (Yelahanka)

IndiaPosted 1 month ago
Data Science And StatisticsStaff+Full Time; Regular
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Date Posted: 2026-06-23Country: IndiaLocation: IN-KA-BENGALURU-NORTHGATE ~ Sy No 2/2 Venkatala Village ~ SY NO 2/2 VENKATALA VILLAGE, Yelahanka HobliPosition Role Type: Hybrid What You Will Do: Guide the team on the PHM approaches & give technical solutions to complex problems. Develop physics-based analytics & physics informed machine learningbased analytics for sensory data from aircraft systems (e.g., engines, actuators, fuel and air conditioning systems). What You Will Learn: Understanding of different aircraft systems, failure modes & its sensor signals Analyze and process large-scale time-series data using Databricks, PySpark, and distributed computing frameworks. Develop fault detection, degradation tracking, and anomaly detection algorithms using statistical and ML methods. Feature engineering, dimensionality reduction, and signal fusion across multiple sensors and systems Qualifications You Must Have: Bachelors / masters in mechanical /Aeronautical / Electrical / Data Science Qualifications We Prefer Bachelors / masters in mechanical /Aeronautical / Electrical / Data Science Job Description: Work closely with SMEs, design engineers, and PHM teams to understand the physical behavior of systems and translate it into analytical models. Analyze and process large-scale time-series data using Databricks, PySpark, and distributed computing frameworks. Develop fault detection, degradation tracking, and anomaly detection algorithms using statistical and ML methods. Integrate physics-based features (derived from thermodynamics, fluid mechanics, or system modeling) with ML models for improved interpretability and accuracy. Perform feature engineering, dimensionality reduction, and signal fusion across multiple sensors and systems. Validate and verify analytics using test data and SME feedback, ensuring physical consistency and robustness. Collaborate in the development of digital twins, prognostics and health management (PHM) models, and predictive maintenance fra .

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