Data Scientist

📋 Description

• Own feature engineering roadmap for ETA & Destination Forecast across 4 commodities.
• Propose and implement features as dbt models using Airflow for pipelines.
• Design and run experiments with kpler-ml; log with MLflow; compare to prod baseline.
• Collaborate with market analysts and product stakeholders to prioritise experiments.
• Contribute to drift monitoring; validate PSI/KS thresholds using MLflow.
• Document experiment decisions in MLflow and Confluence.

🎯 Requirements

• 2+ years ML in production environments, not just research.
• Experience with geospatial or sequential data (vessel trajectories, H3/S2).
• Python proficiency to implement features, write dbt models, and script experiments.
• Familiarity with MLflow or alternative trackers (Weights & Biases, Neptune).
• Nice to have: maritime domain knowledge; Redshift or columnar warehouses with dbt.

🎁 Benefits

• Hybrid work arrangement with flexibility.
• Global team of 850+ experts from 69 countries.
• Work on production ML for cargo intelligence used by analysts and traders.
• Inclusive, collaborative culture with strong support for growth.