About this role
Join the Liquids Data Operations team to help scale our bunker tracking product from existing established hubs to additional bunkering centres worldwide.
This is a hands-on data analytics internship with exposure to shipping/commodities domain logic, geospatial filtering, and operational automation.
• Increase Geographical Coverage: Expand the current bunker tracking model (python-based) to other hubs, including conducting exploratory work to fine-tune for each hub’s nuances • Perform Routine Backtesting: Validate modelled bunker activity by exporting analysis-ready CSVs and reconciling monthly estimates against official port statistics, industry publications, or other trusted external sources. • Investigate Data Quality Issues: Routinely analyze the bunker tracking data set to identify structural data quality issues and develop improvement solutions in the pipeline / post-processing to resolve them. • Improve Pipeline & Data Platform: Help mature how we develop, run and persist bunker pipelines so that expansion is maintainable and scalable.
Essential: • Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field. • Practical experience with Python for data processing (coursework, personal projects, or prior internship acceptable). • Comfort working with SQL (queries, joins, basic schema concepts) and tabular data (CSV/Excel-style analysis). • Ability to work independently on defined tasks while asking targeted questions when domain or data ambiguity arises. Desirable: • Exposure to pandas, SQLAlchemy, or similar data stack used in ETL pipelines. • Familiarity with Git, pull requests, and collaborative code review. • Interest in or prior exposure to shipping, energy commodities, maritime AIS, or geospatial data. • Experience with CLI tools, environment variables, and cloud/database connectivity (PostgreSQL preferred). • Basic understanding of automated workflows (e.g. GitHub Actions) or Google Sheets/API integrations.
This is a hands-on data analytics internship with exposure to shipping/commodities domain logic, geospatial filtering, and operational automation.
• Increase Geographical Coverage: Expand the current bunker tracking model (python-based) to other hubs, including conducting exploratory work to fine-tune for each hub’s nuances • Perform Routine Backtesting: Validate modelled bunker activity by exporting analysis-ready CSVs and reconciling monthly estimates against official port statistics, industry publications, or other trusted external sources. • Investigate Data Quality Issues: Routinely analyze the bunker tracking data set to identify structural data quality issues and develop improvement solutions in the pipeline / post-processing to resolve them. • Improve Pipeline & Data Platform: Help mature how we develop, run and persist bunker pipelines so that expansion is maintainable and scalable.
Essential: • Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field. • Practical experience with Python for data processing (coursework, personal projects, or prior internship acceptable). • Comfort working with SQL (queries, joins, basic schema concepts) and tabular data (CSV/Excel-style analysis). • Ability to work independently on defined tasks while asking targeted questions when domain or data ambiguity arises. Desirable: • Exposure to pandas, SQLAlchemy, or similar data stack used in ETL pipelines. • Familiarity with Git, pull requests, and collaborative code review. • Interest in or prior exposure to shipping, energy commodities, maritime AIS, or geospatial data. • Experience with CLI tools, environment variables, and cloud/database connectivity (PostgreSQL preferred). • Basic understanding of automated workflows (e.g. GitHub Actions) or Google Sheets/API integrations.
Tech stack
PythonPostgreSQL
About Kpler
Kpler is hiring for the fuel oils / bunker analyst intern role. NewJob aggregates active openings directly from Kpler's applicant tracking system, so this listing is current.
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