About the job

About the Role

Enervest is an international energy trading company active in crude oil and refined products derivatives markets. We are looking for a highly motivated oil derivatives analyst to join our oil trading team.

The role will focus on developing quantitative tools, improving oil market fundamental models, and supporting the buildout of supply and demand balances across crude oil and refined products. This is ideal for someone with strong Python skills, a solid econometrics background, and a strong interest in commodities, energy markets, and trading analytics.

Key Responsibilities

The analyst will support the oil trading team across several analytical and technical workstreams, including:

• Modeling fundamental oil market variables, including supply, demand, refinery runs, inventories, trade flows, pricing indicators, and arbitrage signals.
• Developing forecasting models using econometric and statistical techniques.
• Collecting, cleaning, and structuring large datasets from public and proprietary sources.
• Producing charts, dashboards, and reports to support market analysis and trading decisions.
• Working closely with traders and analysts to translate market questions into quantitative frameworks.
• 7+ Years experience.

Required Skills and Experience

Fluent in PythonStrong background in econometricsAbility to work with large heterogeneous datasets.Familiarity with database management, preferably SQL.Ability to communicate technical results clearly and concisely.

Preferred Qualifications

Experience with forecasting models such as OLS, ARIMA/SARIMA/SARIMAX, VAR, panel regression, or machine learning methods.Knowledge of crude oil, refined products, refinery economics, inventories, trade flows, or supply/demand balances.Experience with web scraping, APIs, scheduled tasks, or data pipeline automation.Familiarity with PostgreSQL, SQLAlchemy, Git, Jupyter, or VS Code.

Candidate Profile

The ideal candidate is quantitative, curious, and comfortable combining market logic with coding. They should be able to move from raw data to a clean model or analytical output, while questioning data quality, assumptions, and economic interpretation.

What You Will Gain

Hands-on experience within an oil trading environment.Exposure to real-world commodity market datasets and trading analytics.Practical experience building models used in market research and trading decision support.Opportunity to strengthen Python, econometrics, database, and energy market skills.

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