Data Scientist

Posted 96ds ago

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Job Description

Data Scientist transforming large-scale logistics data into business insights for Catena Clearing. Collaborating with cross-functional teams to empower product direction and customer success through data.

Responsibilities:

  • Analyze large-scale telematics and execution data across fleets, lanes, and time
  • Identify patterns in capacity, utilization, dwell, reliability, HOS, and asset behavior
  • Develop metrics and summaries that reflect real-world freight performance
  • Build and maintain large-scale sandboxes (1,000+ vehicles) using masked or synthetic data
  • Create compelling examples for sales, pilots, and customer conversations
  • Partner with GTM to turn raw data into clear ROI stories and proof points
  • Surface data-driven insights that influence roadmap priorities
  • Validate assumptions about customer use cases with real network data
  • Help define “decision-grade” metrics that customers actually trust
  • Work closely with product, engineering, and FDEs to understand data nuances
  • Support pilots and strategic accounts (e.g., TMS, visibility, broker platforms)
  • Translate technical findings into clear narratives for non-technical audiences
  • Help define data quality checks, thresholds, and confidence measures
  • Assist in shaping normalized views (lane history, asset identity, availability)
  • Focus on interpretability and usability over black-box modeling

Requirements:

  • 3–6+ years in data science, analytics, or applied research roles
  • Experience in logistics, supply chain, marketplaces, or networked platforms is a big plus
  • Strong analytical foundation with experience in Python, SQL, and data analysis workflows
  • Comfort working with large, messy, real-world datasets
  • Ability to reason about operational systems using imperfect data
  • Experience turning analysis into clear business insights and narratives
  • Strong communication skills across technical and non-technical teams
  • Comfortable working in ambiguity and early-stage environments.

Benefits:

  • Professional development opportunities