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Tier-1 Airbus brand, metro location and early-mid level increase competition, though niche propulsion ML reduces it.
Strong aerospace propulsion and safety domain requirements limit cross-industry transferability.
Mandatory propulsion/aerospace experience, safety and Skywise skills create strict technical shortlisting filters.
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Analyze propulsion system data from Post Flight Reports and logbooks to monitor safety-related KPIs using Airbus Skywise or equivalent platforms.
Develop and implement KPIs, dashboards, and predictive maintenance algorithms through data analysis, feature engineering, and root cause analysis to improve propulsion system safety and operational effectiveness.
Communicate analytic results and actionable insights to business and functional leaders using data visualizations to support safety decisions and process/product improvements.
B.Tech./B.E./M.Tech./M.E. degree in aerospace, mechanical, electrical, or electronics engineering.
Minimum 2 years of professional experience in Aerospace or Propulsion systems.
Proficiency in data analytics tools and techniques including Python, Matlab, R; experience with data wrangling/data mining and scripting languages (Python, Java, C).
Awareness or experience with Skywise or equivalent data platforms; understanding of propulsion systems, FMECA/RCA analysis, aviation safety/airworthiness requirements, system engineering, and reliability concepts.
Has strong understanding of propulsion systems to identify non-obvious anomalies or correlations for predictive maintenance and safety analysis.
Experienced in applying machine learning, generative AI, or LLMs for large dataset analytics within aerospace or propulsion contexts.
Comfortable working independently and collaboratively in a technologically transitional environment, with skill in translating complex technical data into actionable business insights.