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- Tasks: Develop and maintain data-driven models for the dry bulk freight market.
- Company: Join Kpler, a leader in market insights with a diverse and inclusive culture.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career development.
- Why this job: Make an impact by translating complex data into actionable insights for clients.
- Qualifications: Experience in time series forecasting and programming skills in Python or R.
The predicted salary is between 50000 - 70000 £ per year.
Your future position Kpler is 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.
Your mission is to:
- 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
You could be a match if you are or have:
- 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
Desirable:
- 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
Kpler is committed to providing a fair, inclusive and diverse work‑environment. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.
Our People Pledge: Don’t meet every single requirement? Research shows that women and people of colour 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.
Quantitative Freight Analyst - Dry Bulk employer: Medium
Contact Detail:
Medium Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Freight Analyst - Dry Bulk
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend relevant events, and connect with Kpler employees on LinkedIn. Building relationships can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or models you've built, share them during interviews or even on your LinkedIn profile. It’s a great way to demonstrate your expertise in time series forecasting and data analysis.
✨Tip Number 3
Prepare for the interview by understanding Kpler's products and services. Familiarise yourself with their dry bulk freight market insights and think about how your skills can contribute to their goals. This shows you're genuinely interested!
✨Tip Number 4
Don’t forget to follow up after interviews! A quick thank-you email reiterating your interest in the role and highlighting a key point from your conversation can keep you top of mind for the hiring team.
We think you need these skills to ace Quantitative Freight Analyst - Dry Bulk
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with time series forecasting models and any relevant programming skills. We want to see how your background aligns with the role of a Quantitative Freight Analyst.
Showcase Your Analytical Skills: In your application, emphasise your ability to translate complex quantitative outputs into actionable insights. We’re looking for candidates who can demonstrate their analytical prowess and problem-solving skills in real-world scenarios.
Be Authentic: Don’t be afraid to let your personality shine through in your written application. We value diverse perspectives and want to get a sense of who you are beyond your qualifications. Share your passion for the dry bulk freight market!
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. This helps us keep track of applications and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Medium
✨Know Your Models
Make sure you’re well-versed in time series forecasting models, especially those related to freight rate movements. Be ready to discuss your experience with these models and how you've applied them in real-world scenarios.
✨Showcase Your Programming Skills
Brush up on your programming skills in Python, R, or any JVM-based language. Be prepared to talk about specific projects where you’ve used these languages to build analytical tools or automate processes.
✨Translate Complexity into Simplicity
Practice explaining complex quantitative outputs in a way that’s easy to understand. Think of examples where you’ve successfully communicated insights to non-technical stakeholders, as this will be crucial for the role.
✨Demonstrate Ownership and Problem-Solving
Be ready to share instances where you took ownership of a project or problem. Highlight your pragmatic approach to solving issues and how you iterated towards effective solutions, as this aligns with the company’s values.