Job Description

Off-Cycle Trading Intern - Quantitative (Data & Platform)

Off-Cycle Trading Intern - Quantitative (Data & Platform)

We're hiring an off-cycle intern to own data ingestion and update workflows that support our energy analytics. You will be responsible for pulling data from providers, maintaining datasets, and automating processes. Your activities will be an integral part of our analytics processes.

Primary responsibilities

Pull, clean, and update datasets from vendor APIs/feeds (e.g., REST/FTP/CSV/Parquet), and internal sources. This will include various fundamental datasets, market data and alternative data, structured, semi-structured and unstructured data. Maintain daily/weekly update scripts; perform manual updates/checks where needed. Build resilience and robustness into update processes. Build Python utilities to automate repetitive tasks (ingestion, validation, transformations, exports) Implement basic data quality checks (schema validation, null/outlier checks, freshness, completeness) Package and deliver clean datasets to researchers/traders; keep metadata and change logs current Create dashboards and reports (e.g., status, exceptions),communicate issues/escalations promptly Improve reliability and speed of existing pipelines (error handling, retries, logging, data integrity and completeness) Document workflows and handoffs to ensure smooth operations

Requirements:

Currently enrolled in a BA/BS or MSc in Computer Science, Data Science, Engineering, Mathematics, or related field Strong Python (pandas, requests, pathlib, typing); comfort with JSON/CSV/Excel/Parquet Practical data-wrangling skills and attention to detail Basic SQL and familiarity with Git and Linux/command line Clear communicator with a proactive, ownership mindset * Ability to commit to a 6-month internship commencing from January 2026