Data Scientist (Logistics)

TL;DR

Data Scientist (Logistics): Transforming large-scale, multi-source supply chain datasets into decision-ready information assets with an accent on data ingestion, quality assessment, and pipeline development. Focus on applying statistical and machine learning models to identify predictive signals in freight, inventory, and supplier performance.

Company

hirify.global (BridgeNet Solutions) provides sourcing, analytics, and technology solutions for Fortune 500 and Global 2000 companies to optimize complex global supply chains.

What you will do

• Ingest, profile, and validate large-scale supply chain datasets from ERP systems, TMS platforms, and carrier feeds.
• Identify and document data quality issues and develop root-cause analyses to implement remediation strategies.
• Monitor incoming supplier and LSP data feeds to ensure structural consistency and data integrity.
• Develop analytical baselines for key domains including freight cost, carrier performance, and inventory utilization.
• Apply statistical and machine learning models to identify patterns, outliers, and predictive signals within supply chain data.
• Translate analytical findings into actionable recommendations for non-technical stakeholders and client leadership.

Requirements

• Experience operating at the intersection of data engineering, statistical modeling, and operational supply chain knowledge.
• Proficiency in end-to-end data ingestion, quality assessment, and pipeline development.
• Ability to design gap-filling methodologies, imputation techniques, and cleansing rule sets.
• Experience developing predictive models for shipment lead times and supplier performance trends.
• Ability to deliver model outputs in structured, consumable formats for operational dashboards and reporting.
• Strong documentation skills for transformation logic, model assumptions, and data limitations.