Associate Analyst, Linehaul Analytics - Hybrid

XPO•Boston, MA

5d•$70,889 - $88,611•Hybrid

About The Position

The Associate Analyst, Linehaul Analytics will help improve model reliability by designing and maintaining analytical test cases, validation scripts, and metric checks for optimization workflows, simulators, and operational decision-support tools. In the first year, the focus will be on testing, validating, and analyzing existing linehaul optimization models and simulator outputs. This role will serve as a ramp-up period to learn the internals of the models, data, network behavior, and operational constraints. Over time, the analyst will expand into building analytical tools, dashboards, early-warning systems, network path assessments, simulator improvements, and performance metrics that help the team better understand and improve linehaul optimization outcomes. The role involves building and maintaining analytical tools, dashboards, and monitoring metrics that provide visibility into optimization model performance, linehaul network health, shipment flow, service center volume, consolidation opportunities, and shipment diversions. The analyst will analyze linehaul optimization model outputs, operational data, and network behavior to identify data-quality issues, inconsistencies, anomalies, and performance gaps using Python, pandas, SQL, and traditional data analytics tools. They will support the development of internal tools used to evaluate linehaul paths, routing behavior, simulator results, and operational tradeoffs. Collaboration with optimization modelers, engineers, and operations stakeholders is key to turning ambiguous problems into clear analyses, reliable metrics, and actionable insights. The analyst will investigate complex operational issues across shipment patterns, routing decisions, network constraints, and service center capacity to determine root causes and recommend practical improvements. Findings will be communicated clearly through written analysis, root-cause investigation, metrics, dashboards, and actionable recommendations.

Requirements

Bachelor’s degree or equivalent related work or military experience
Strong Python skills, including experience with pandas or similar data analysis libraries.
Experience working with structured data, large datasets, and data-quality validation.
Strong analytical and problem-solving skills, with the ability to reason through complex operational systems and identify non-obvious relationships.
Ability to investigate anomalies, validate assumptions, and explain findings using data, logic, and reproducible analysis.
Comfort working with metrics, dashboards, reports, validation scripts, and operational data workflows.
Ability to break down ambiguous business or operational problems into clear analytical steps.
Strong written and verbal communication skills, including the ability to explain technical findings to both technical and non-technical stakeholders.

Nice To Haves

Master’s degree in Data Analytics, Engineering, Mathematics, Operations Research, Computer Science, Statistics, Logistics, Supply Chain, or a related field; or 2+ years of relevant professional experience.
Experience with SQL and relational data concepts.
Experience building dashboards, monitoring tools, or recurring analytical reports.
Experience with logistics, transportation, supply chain, routing, linehaul, network planning, or operations analytics.
Experience validating optimization models, simulation outputs, or decision-support systems.
Experience with Python-based analytics, automation, or test frameworks.
Familiarity with C++ or another high-performance language for speeding up data-intensive tools or simulators.
Experience identifying root causes in complex systems with multiple interacting factors.
Exposure to service center operations, shipment consolidation, shipment diversion, routing networks, or capacity planning.
Experience creating new metrics or tools from scratch when existing reporting is insufficient.

Responsibilities

Help improve model reliability by designing and maintaining analytical test cases, validation scripts, and metric checks for optimization workflows, simulators, and operational decision-support tools.
Primarily focus on testing, validating, and analyzing existing linehaul optimization models and simulator outputs.
Expand into building analytical tools, dashboards, early-warning systems, network path assessments, simulator improvements, and performance metrics.
Build and maintain analytical tools, dashboards, and monitoring metrics that provide visibility into optimization model performance, linehaul network health, shipment flow, service center volume, consolidation opportunities, and shipment diversions.
Analyze linehaul optimization model outputs, operational data, and network behavior to identify data-quality issues, inconsistencies, anomalies, and performance gaps using Python, pandas, SQL, and traditional data analytics tools.
Support development of internal tools used to evaluate linehaul paths, routing behavior, simulator results, and operational tradeoffs.
Collaborate with optimization modelers, engineers, and operations stakeholders to turn ambiguous problems into clear analyses, reliable metrics, and actionable insights.
Investigate complex operational issues across shipment patterns, routing decisions, network constraints, and service center capacity to determine root causes and recommend practical improvements.
Communicate findings clearly through written analysis, root-cause investigation, metrics, dashboards, and actionable recommendations.