Data Scientist / Data Analytics Engineer
Remote · United States
Job Summary
Design, train, validate, and deploy predictive models (regression, classification, time-series forecasting, survival analysis, clustering, anomaly detection, and gradient-boosted / deep learning approaches as appropriate) and develop point-in-time analytics, KPI scorecards, and operational dashboards to support dispatch, fleet, customer success, finance, and product teams. Build and maintain reusable analytical datasets, semantic layers, and certified metrics; design and operate data pipelines on AWS (Redshift, S3, Glue, Lambda, Step Functions, Kinesis, EMR, Athena, SageMaker); implement medallion and STARR models; ensure model monitoring, explainability, data quality, and production readiness. Collaborate across product, engineering, operations, and commercial teams to embed analytics into workflows and customer-facing applications; mentor analysts and engineers on statistical rigor, modeling best practices, and modern data architecture.
Required Qualifications
- Bachelor's degree in Statistics, Mathematics, or Supply Chain Management; a degree in Computer Science is also acceptable.
- Master's degree preferred but not required.
- Professional experience in the transportation, trucking, freight, logistics, or broader supply chain industry, with working knowledge of loads, stops, shipments, ELD/telematics, TMS, dispatch, billing, etc.
- Experience taking customer-facing analytics products or features from idea through implementation and launch, including product discovery, scoping, model and metric design, partnering with product/engineering, and supporting the feature in production with real customers.
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