Job Description:
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.
• - AWS: SageMaker, S3, Glue, EMR, Lambda, Step Functions, CloudWatch.
• - Streaming/event data: Kafka/MSK or Kinesis, Spark Structured Streaming/Flink.
• - MLOps: MLflow/Kubeflow/SageMaker, CI/CD, IaC.
• - 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:
• - FOQA, QAR/DFDR, ACMS, AID, ATA chapters, MSG-3/CBM, AMOS/RAMCO/TRAX.
• - 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
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