Data Scientist

The Commodities tribe at Kpler runs production ML models that predict what cargo a vessel is carrying (Product Estimation) and where in-transit vessels are headed (Destination Forecast), and where they are expected to arrive (ETA)— across LNG, DRY, LPG, and LIQUIDS. These predictions feed directly into Kpler's cargo intelligence platform, consumed by market analysts, trading desks, and external customers worldwide.

You will own the science behind these models: designing and evaluating features from maritime AIS data, H3 geospatial routing distributions, transit statistics, and commodity-specific signals; running structured experiments on ML Flow based platform; and pushing the accuracy, coverage, and reliability of predictions forward.

You are not handed a Jupyter notebook and a dataset. You work in a production system with real-time inference running every 1–3 hours across 4 commodity types, and your model changes need to be validated against a running parallel baseline before they go live. The new platform is being built specifically to make the experiment loop fast enough that this level of rigour does not slow you down.