Quantitative Researcher
Listed on 2026-10-20
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Business
Data Scientist
HSE PCOM seeks to add Quantitative Researcher to our proprietary trading team. This is a ground-floor opportunity for a recent graduate with a rigorous quantitative background who wants to build something from scratch in a fast-moving, high-conviction environment. You will work shoulder-to-shoulder with the founding traders and portfolio managers, developing the models, analytics, and data infrastructure that will power our trading across US power, natural gas, and renewables markets.
The Quantitative Researcher is expected to be a self-starter who is expected to identify problems, propose solutions and execute with the mentorship and support of experienced practitioners around you.
- Build, test, and maintain quantitative models for pricing, forecasting, and risk management across US power (ISO/RTO markets), natural gas (Henry Hub, basis, transport), and renewable energy products
- Develop and execute quantitative research workflows within Linux-based environments (Ubuntu, RHEL), leveraging the command line, shell scripting, and standard tooling for data processing and analysis
- Analyze large-scale datasets including load forecasts, generation stacks, weather models, pipeline flows, congestion patterns, and renewable output to generate actionable trading signals
- Devise cutting-edge techniques for storage and retrieval and parsing of data
- Develop complex models using this data to develop fundamental views and signals
- Conduct fundamental and statistical research on US energy supply/demand dynamics, capacity markets, renewable penetration trends, storage economics, and regulatory or policy shifts (FERC, state RPSs, IRA incentives)
- Support back-testing of trading strategies, P&L attribution analysis, and portfolio risk reporting
- Use AI tools to automate workflows for code development and management
- Bachelor’s degree in engineering (Computer Science, Applied Mathematics, Electrical, Mechanical, Meteorology or similar) or hard sciences (Physics or Mathematics)
- Strong foundation in probability, statistics, linear algebra, and numerical methods
- Comfortable working in Linux environments (Ubuntu, RHEL) for day-to-day development, data processing, and research workflows, including proficiency with the command line, shell scripting, and common tooling (cron, ssh, tmux, etc.)
- Self-starter mentality — proven ability to work independently, take initiative, and thrive with minimal structure in a fast-paced environment
- Strong written and verbal communication skills; ability to distill complex analysis into clear, concise recommendations
- Intellectual curiosity about energy markets and a genuine interest in trading
- Hands‑on knowledge of AI/ML and stats packages such as PyTorch, sklearn as well as using LLM based tools such as Cursor, Claude Code.
- Strong programming background (Python preferred) with familiarity with Linux OS and relational databases
- Master’s or a Ph.D. in quantitative discipline (Computer Science, Applied Mathematics, Electrical, Mechanical, Meteorology or similar) or hard sciences (Physics or Mathematics)
- Experience with cloud computing platforms (AWS/GCP/Azure), or large-scale data processing tools (Spark, Airflow)
- Understanding of derivatives fundamentals — options, swaps, futures, and spread structures relevant to energy commodities
- Exposure to market data platforms such as Bloomberg, Grid Info etc.
- Exposure to weather data
Hull Street Energy PCOM Services, LLC (“HSE PCOM”) is a power generation company operations management company that manages investment holdings across multiple private equity funds and acquisition vehicles affiliated with Hull Street Energy, LLC (together with HSE PCOM,…
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