Company
Oil & Chemicals
FuelOils/BunkerAnalystIntern
Neural analysis suggests this role is
optimal for Entry candidates.
“Fuel Oils / Bunker Analyst Intern. Skills: Data analytics, Python, SQL. Expand bunker tracking model. Conduct exploratory work”
Industry & Context.
Data quality analysis; Develop improvement solutions
What They're Looking For.
Must Have
Degree in Computer Science, Degree in Data Science, Degree in Engineering, Degree in Statistics, Python for data processing, Comfort working with SQL, Tabular data analysis, Ability to work independently
Nice to Have
Exposure to pandas, Exposure to SQLAlchemy, Familiarity with Git, Familiarity with pull requests, Interest in shipping, Interest in energy commodities, Interest in maritime AIS, Interest in geospatial data, Experience with CLI tools, Experience with environment variables, Experience with cloud connectivity, Experience with database connectivity, Basic understanding of automated workflows, Basic understanding of Google Sheets integrations, Basic understanding of Google Sheets API integrations
What You'll Do.
Expand bunker tracking model
Conduct exploratory work
Fine-tune model for hubs
Validate modelled bunker activity
Export analysis-ready CSVs
Reconcile monthly estimates
Analyze bunker tracking data set
Identify structural data quality issues
Develop improvement solutions
Mature bunker pipeline development
Mature bunker pipeline execution
Mature bunker pipeline persistence
Full Job Description
## Description 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. ## Key Responsibilities 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.
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