Own the feature engineering roadmap for ETA & Destination Forecast across all 4 commodity types.
Propose and implement new features as dbt models using Airflow to orchestrate the data pipelines.
Validate their impact through structured experiments.
Design and run experiments using kpler-ml framework.
Work directly with Commodities Market Analysts and product stakeholders.

2+ years applying ML to real-world production problems — not research or hackathon work, but models running in production with real consequences for errors
Experience with geospatial or sequential data — vessel trajectories, routing patterns, H3/S2 grid systems, or equivalent spatial representations
Python proficiency at a level sufficient to implement new features, write dbt models, and script experiments — not just use notebooks
Familiarity with MLflow or equivalent experiment tracking (Weights & Biases, Neptune, etc.)
Desirable: Domain knowledge of maritime shipping, commodity trading, or cargo intelligence
Familiarity with Redshift or columnar warehouses for large-scale feature queries and dbt (authoring or reading SQL models)

We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on.
Inclusive and diverse work environment.
Access to cutting-edge innovation for impactful results.

Data Scientist

Key skills