Commercial Graduate Scheme, Junior Data Scientist - Dubai, UAE

AI in this role

langchain

ragllm-integration

Employment Type: Full-time & Permanent.

Job Location: Dubai, UAE (We provide visa sponsorship & relocation assistance).

Salary: USD 65,000 per annum + performance based bonus - 0% tax environment.

Employee Share Scheme: Opportunity to join Cobblestone Employee Share Scheme.

Annual Leave: 30 Calendar Days.

Public Holidays: As declared by UAE Government annually (8 to 14 days).

Probation Period: 3 to 6 Months (as per UAE Labour Law).

Health Insurance: Comprehensive Private Health Insurance (IPD, OPD & Dental).

Residency Visa Sponsorship: Provided by the Company.

Relocation Support: Available for candidates relocating to Dubai.

End of Service Gratuity: As per UAE Labour Law.

About Cobblestone Energy

Cobblestone Energy is an energy trading company specialising in the European Gas, Power and Emissions markets. Established in 2018, we combine deep analytics, advanced data science and agile technology to drive profitable trading decisions. Our flat organisational structure empowers every team member with autonomy and ownership. Our diverse global team of extraordinary talent is united by a relentless pursuit of excellence.

Cobblestone Values

Excellence in Hiring & Teamwork
Lifelong Learning Through Continuous Reflection
Independent Thinking Through a Meritocracy of Ideas
Winning

What we offer in this role

A full-time position on our Commercial team
Committed and remarkably talented colleagues.
Highly competitive compensation dependent on performance
An exciting, challenging and fulfilling career.
Investment in your development to ensure that you always remain the best in business.
Equity participation for strong contributors, ensuring our interests are all aligned long term.

Key Responsibilities:

Data Preparation: Collect, clean, and structure large datasets from market, fundamental, and operational sources
Forecasting & Modeling: Develop and validate predictive models (e.g. wind generation, demand) to support trading strategies
Strategy Research: Prototype, back-test, and refine data-driven trading ideas; collaborate with analytics and development teams to productionise solutions
Infrastructure: Build and maintain data pipelines, dashboards, and automated tooling to streamline workflows
AI-Accelerated Workflows: Utilise LLMs and agentic frameworks to accelerate exploratory data analysis (EDA), automate data cleaning pipelines, and generate synthetic data for model robustification.
Stay current with the rapidly evolving AI landscape (e.g., RAG, Agents, Multimodal models) and proactively propose new ways to apply these to trading data.
Collaboration: Partner with traders, risk managers, and software engineers to integrate insights into real-time decision-making
Documentation: Maintain clear records of methodologies, data definitions, and model specifications
Culture: Champion our values through proactive communication and teamwork

Your background:

Bachelor's or master’s degree in Computer Science, Mathematics, Statistics, or a related field
Strong proficiency in programming languages such as Python and R
Experience with data analysis and manipulation tools such as Pandas, NumPy, and SQL
Knowledge of data visualization tools such as Matplotlib and Seaborn
Experience programmatically integrating LLMs (via APIs, LangChain, or Python scripts) into data pipelines rather than just using chat interfaces.
Proven ability to build custom "Agents" or automated workflows that interpret unstructured data or reason through multi-step problems.
Pro-active and flexible work mentality
Interest in data-driven trading
Fluency in English, both written and spoken.

Preferred Background:

Proven track record of excellence, academic or professional, in quantitative or analytical roles
Experience working with time-series data, machine learning libraries, or cloud-based data platforms
Demonstrated ability to innovate and drive end-to-end solutions

The Hiring Process

Application Review
Online Assessments: Psychometric and logical reasoning tests
Case Study: Research-oriented project to showcase your analytical approach
Remote Interviews: Three rounds with members of our Analytics and Trading teams
Offer & Onboarding: Join our Commercial Development Program, then step directly into your role as Junior Data Scientist

Learn more about Cobblestone Energy careers:
https://cobblestoneenergy.com/careers/

Why work with us:
https://cobblestoneenergy.com/why-work-with-us/

Recruitment process:
https://cobblestoneenergy.com/careers/vacancies/#process

How we rate this

Commercial Graduate Scheme, Junior Data Scientist - Dubai, UAE at Cobblestone Energy rates 41 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGLLM IntegrationLangChain

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How have you integrated a large language model into a production application?
What are the limits of LangChain that you've run into, and how did you work around them?
This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
Tell me about a time an AI tool got something wrong. How did you catch it?

Adapt your resume

List these exact terms on your resume: RAG, LLM Integration, and LangChain. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Put the AI tool in a bullet point about what you did, not just in a skills list — this role treats it as a required part of the job.

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