Sr. Data Scientist

Must be a US Citizen or Hold a Green Card

ABOUT THE ROLE

We are looking to hire a Data Scientist who can transform the complexity of global shipping and logistics into clear, actionable intelligence. You'll work across operations, engineering, and leadership to build predictive systems that optimize routes, forecast demand, and surface insights that keep cargo moving. This is a high-impact role at the intersection of data science, operational expertise, and emerging AI.

CORE REQUIREMENTS

This candidate will have Dashboard & BI Tooling. Being Fluent in

Tableau, Power BI, Looker, or equivalent. They will be able to model data and present it for both technical and executive audiences.

They will have Complex Data Fluency. Being very comfortable wrangling large, noisy datasets --- EDI records, tracking logs, port data, weather overlays, and multi-model feeds.

They will do Predictive Modeling. Having proven experience building

ML models from messy. High-dimensional datasets (time series, sensor data, ETA prediction, etc.).

They will be well versed in AI & Machine Learning. Having Hands-On experience with LLM’s, NLP, computer vision, or operations research applied to real-world logistics problems.

This candidate must also be excellent in Collaboration &

Communication. They can translate model outputs into business decisions. They will also possess strong documentation habits and cross-functional alignment skills.

WHAT YOU'LL WORK ON

Route optimization and transit time prediction models · Anomaly detection in shipment and carrier data · Real-time operational dashboards for fleet and port performance · AI-assisted demand forecasting for freight capacity planning · Cross-team data infrastructure and model deployment support.

REQUIREMENTS

6+ Years in shipping, freight, logistics, or supply chain,

Understand how cargo and data both move.

NICE TO HAVES

Python, R, or SQL --- scripting and querying at production scale.

Software Development Principles: version control (Git), CI/CD, API integration. Familiarity with containerization (Docker) or cloud platform (AWS, GCP, Azure). Experience building data pipelines or ETL workflows.