Data Scientist (ML)

TL;DR

Data Scientist (ML/Geospatial): Building and optimizing production ML models for cargo estimation, destination forecasting, and ETA predictions with an accent on geospatial feature engineering and real-time inference. Focus on designing H3 routing distributions, implementing dbt models for data pipelines, and validating model accuracy against production baselines.

Location: Hybrid in London, Greece, or Hungary

Company

hirify.global provides high-quality cargo intelligence and data analytics for market analysts and trading desks worldwide.

What you will do

• Own the feature engineering roadmap for ETA and Destination Forecast across four commodity types.
• Implement new features as dbt models using Airflow to orchestrate data pipelines.
• Design and run ML experiments using the hirify.global-ml framework and MLflow, producing structured comparison reports.
• Collaborate with Market Analysts and product stakeholders to prioritize the experiment backlog based on commercial impact.
• Develop and validate drift monitoring using PSI/KS thresholds against historical inference batches.
• Document all experiment decisions and history in MLflow and Confluence.

Requirements

• 2+ years of experience applying ML to real-world production problems.
• Experience with geospatial or sequential data, such as vessel trajectories or H3/S2 grid systems.
• Proficiency in Python for implementing features, writing dbt models, and scripting experiments.
• Familiarity with MLflow or equivalent experiment tracking tools (Weights & Biases, Neptune).
• Must be based in or able to work from London, Greece, or Hungary (Hybrid).

Nice to have

• Domain knowledge of maritime shipping, commodity trading, or cargo intelligence.
• Experience with Redshift or similar columnar warehouses for large-scale feature queries.
• Ability to author or read complex SQL models in dbt.