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.
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