Data Scientist

Kpler· Greece, Hungary, London· lever· veröffentlicht 06.07.2026
Muss:PythonAILeadPrincipal
At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.   Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success. Key Responsibilities 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, and validate their impact through structured experiments. Design and run experiments using kpler-ml framework, logging all runs from train to evaluation to MLflow and producing structured comparison reports against the production baseline before any promotion. Work directly with Commodities Market Analysts and product stakeholders to understand where prediction quality matters most commercially — and use that to prioritise the experiment backlog. Contribute to the drift monitoring setup — validate PSI/KS thresholds using MLFlow against historical inference batches; define what constitutes a meaningful drift signal for PE and DF specifically. Document experiment decisions in MLflow and Confluence documents — the experiment history is a first-class artifact, not an afterthought. Experience & Background 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 — understanding what a port call sequence or a vessel's draught profile means physically, not just statistically 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. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us?   We make things happen We act decisively and with purpose, going the extra mile.   We build
together We foster relationships and develop creative solutions to address market challenges.   We are here to help We are accessible and supportive to colleagues and clients with a friendly approach.     Our People Pledge   Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.   Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.       By applying, I confirm that I have read and accept the Staff Privacy Notice