Junior Market Data Analyst – Chartering

Your future position

Join Kpler’s Chartering team as a Junior Market Data Analyst – Chartering and play a key role in ensuring the quality and accuracy of the data that powers our Chartering products.

Kpler’s Chartering products rely on accurate vessel, ownership and market data to help charterers, shipowners and brokers make informed commercial decisions. In this role, you will work hands-on with the datasets behind these products, investigating inconsistencies, validating information and helping improve data quality at scale.

Your work will span a range of chartering datasets, from vessel ownership and characteristics to fixtures, cargo orders, vessel positions and shipping zones. You will use SQL and Python to extract, transform and analyse data, build validation checks and investigate potential issues. 

This is a role for someone who enjoys getting into the detail of data, asking why something doesn't look right and finding ways to identify and solve problems systematically. You will work closely with Product, Data, Research, Engineering and AI/ML teams, turning individual data issues into broader improvements across Kpler's datasets and products.

Your mission is to:

Monitor, validate and improve the quality of key datasets supporting Kpler's Chartering products.
Investigate data gaps, inconsistencies and customer-reported issues, using data analysis to understand their root causes and drive them through to resolution.
Curate and validate vessel ownership, commercial management, operator information and relevant vessel characteristics.
Review and benchmark AI-parsed fixtures, identifying recurring extraction errors and building validation approaches to measure and improve parsing quality.
Use SQL to query large datasets, including cargo and AIS data, to investigate potential issues and identify incorrect or inconsistent information at scale.
Use Python notebooks to extract, transform and analyse data and develop validation scripts and repeatable quality checks.
Maintain and improve Kpler's chartering-specific shipping zones and geographical mappings, using tools such as QGIS.
Work with Product, Data, Research, Engineering and AI/ML teams to provide structured feedback and help improve the quality of underlying datasets and extraction processes.
Translate individual data-quality issues into systematic improvements where appropriate, identifying patterns rather than only correcting individual records.
Contribute to the development of new analytical views and algorithms as the Chartering product evolves, including areas such as CPP/DPP and projected vessels.
Help establish and track data-quality metrics, benchmarks and processes as Chartering datasets expand.

Experience & Background:

• 1–3 years of experience in data analysis, market research, maritime/shipping, commodities or a related analytical role.
• Proven hands-on experience with SQL and confidence writing queries to analyse and investigate large datasets.
• Proven hands-on experience with Python, including working in notebooks and using Python for data analysis, transformation or validation.
• Strong Excel / Google Sheets skills.
• Strong analytical and problem-solving skills, with excellent attention to detail and an ability to identify patterns and inconsistencies in data.
• Comfortable working with large datasets and extracting and transforming data to investigate specific questions
Desirable:
Understanding of shipping, chartering or commodity markets.
Familiarity with tanker and/or dry-bulk vessel segments.
Understanding of concepts such as fixtures, vessel positions, cargo orders, vessel ownership and shipping geography.
Experience working with AI/LLM-extracted or other machine-generated datasets.
Experience with maritime data providers, brokers, shipowners, charterers or commodity trading companies.
Behavioural Competencies
• You are naturally curious and want to understand why data is wrong, not just identify that it is wrong.
• You are highly detail-oriented and take a methodical approach to investigating data issues.
• You take ownership of problems and follow them through from investigation to resolution.
• You thrive in an environment where data quality, accuracy and continuous improvement are central to the work.