Global Connect Technologies
Data Scientist- Aviation Experience
Global Connect Technologies, Chicago, Illinois, United States, 60290
Overview
Senior Data Scientist – Aviation Analytics (7+ years) Mandatory Skills
7+ years in Data Science with 3+ years in aviation or large-scale event/time-series domains. Strong in Python, SQL, Spark; hands-on with time-series, anomaly detection, Bayesian methods. Streaming/event data: Kafka/MSK or Kinesis, Spark Structured Streaming/Flink. Model monitoring & explainability (drift, SHAP/LIME). Key Responsibilities
Translate business problems into ML solutions. Build models for time-series forecasting, anomaly detection, survival analysis, clustering, and optimization. Engineer features from flight logs, ACARS, ADS-B, maintenance logs, and weather data. Productionize models on AWS with CI/CD, model registry, feature store, and monitoring. Collaborate with Data Engineering to ensure data quality, lineage, and governance. Communicate insights and model decisions to non-technical stakeholders. Lead advanced analytics and ML initiatives for airlines/aero programs—spanning flight telemetry, aircraft health monitoring, operational efficiency, delay attribution, fuel optimization, and safety insights. Own end-to-end model lifecycle from problem framing to production in AWS (multi-cloud is a plus). Preferred Qualifications
ADS-B, ACARS, IATA SSIM, OOOI timestamps, delay codes, fuel/weight & balance analytics. Safety programs (ASAP/SMS/LOSA), ICAO Annex 19 context; EASA/FAA exposure Seniority level
Mid-Senior level Employment type
Full-time Industries
Aviation and Aerospace Component Manufacturing
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Senior Data Scientist – Aviation Analytics (7+ years) Mandatory Skills
7+ years in Data Science with 3+ years in aviation or large-scale event/time-series domains. Strong in Python, SQL, Spark; hands-on with time-series, anomaly detection, Bayesian methods. Streaming/event data: Kafka/MSK or Kinesis, Spark Structured Streaming/Flink. Model monitoring & explainability (drift, SHAP/LIME). Key Responsibilities
Translate business problems into ML solutions. Build models for time-series forecasting, anomaly detection, survival analysis, clustering, and optimization. Engineer features from flight logs, ACARS, ADS-B, maintenance logs, and weather data. Productionize models on AWS with CI/CD, model registry, feature store, and monitoring. Collaborate with Data Engineering to ensure data quality, lineage, and governance. Communicate insights and model decisions to non-technical stakeholders. Lead advanced analytics and ML initiatives for airlines/aero programs—spanning flight telemetry, aircraft health monitoring, operational efficiency, delay attribution, fuel optimization, and safety insights. Own end-to-end model lifecycle from problem framing to production in AWS (multi-cloud is a plus). Preferred Qualifications
ADS-B, ACARS, IATA SSIM, OOOI timestamps, delay codes, fuel/weight & balance analytics. Safety programs (ASAP/SMS/LOSA), ICAO Annex 19 context; EASA/FAA exposure Seniority level
Mid-Senior level Employment type
Full-time Industries
Aviation and Aerospace Component Manufacturing
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