Junior Data Scientist
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Key skills for this role
About the Role
Collect and analyze data, develop predictive models, build data pipelines, and collaborate with teams; requires proficiency in Python, R, and data visualization.
Key Skills for This Role
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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
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