Quantitative Freight Analyst - Dry Bulk

Kpler are looking for an experienced Quantitative Analyst to develop and maintain data-driven models of the dry bulk freight market.

You will originate and own research ideas, and build analytical tools that leverage Kpler and external data, to deliver market insights to in-house analysts and clients.

A key focus is expanding Kpler's dry freight market forecasts and ton-mile demand projection.

• Develop, deploy, and maintain time series forecasting models for freight rate movements and ton-mile demand
• Build automated, reproducible analysis systems for freight market forecasting
• Originate and own research ideas that advance Kpler's dry bulk freight offering
• Collaborate with engineers and product owners to enhance freight market data and analytical tools
• Identify and evaluate opportunities for future development of freight research capabilities
• Translate complex quantitative outputs into actionable insights for analysts and clients
• Ensure model performance through ongoing monitoring, validation, and iteration
• Demonstrated ability to think in systems: you understand how components interact, feedback loops, and emergent behaviours in complex markets
• Experience developing and maintaining time series forecasting models for freight rate movements
• Some experience programming in Python, R, or a JVM-based language
• Ability to translate complex quantitative outputs into actionable insights
• Good sense of ownership: pragmatic problem-solving skills, constructive critique, and the ability to iterate towards end-to-end solutions
• Fluent in English: excellent communication skills and the ability to work and collaborate in an international, cross-cultural environment
• Knowledge of and experience analysing complex supply chains
• Comfortable retrieving data from APIs and relational databases (PostgreSQL preferred)
• Understanding of the fundamental supply and demand drivers of the dry bulk freight market, how routes are priced, and the roles of commercial players in transactions
• Knowledge of voyage economics or seasonal commodity patterns
• Comfortable using AI coding assistants to accelerate development and problem-solving