Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist specializing in Aviation Analytics, requiring 7+ years of Data Science experience, including 3+ years in aviation. The position is onsite in Chicago, offers a contract of over 6 months, and demands strong skills in Python, SQL, AWS, and MLOps.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 18, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Chicago, IL
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🧠 - Skills detailed
#Clustering #Monitoring #Data Quality #Lambda (AWS Lambda) #Data Engineering #MLflow #Spark (Apache Spark) #Forecasting #AWS (Amazon Web Services) #Anomaly Detection #SQL (Structured Query Language) #Python #SageMaker #ML (Machine Learning) #S3 (Amazon Simple Storage Service) #Infrastructure as Code (IaC) #Cloud #AWS SageMaker #Data Science #Kafka (Apache Kafka)
Role description
Role: Data Scientist
Location: Chicago, Illinois (onsite only)
Job Type: Full time
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
Role: Data Scientist
Location: Chicago, Illinois (onsite only)
Job Type: Full time
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
