Analista de Datos del Mercado Energético (Híbrido)

Placements24; Oaxaca de Juárez; Hybrid; MXN 350,000 - 600,000; Full time

Benefits offered by this job

Hybrid work model

Health benefits

Professional growth opportunities

Advanced analytics tools

Job summary

Placements24 is seeking an Energetic Market Data Analyst in Oaxaca City to transform large energy data sets into actionable insights. You will forecast demand, analyze market dynamics, and support strategic decisions with robust models and clear visuals.

In a hybrid role, you will collaborate with engineering, finance, and strategy teams, using Python/R/SQL and BI tools to deliver data-driven recommendations and compelling presentations.

Qualifications

• Degree in a quantitative field such as Economics, Statistics, Mathematics, Engineering or Finance.
• Master's degree is preferred but not mandatory.
• At least 4 years of experience in data/market analysis or financial modeling, ideally in energy.

Responsibilities

• Collect, clean, and process large datasets on energy production, consumption, pricing and market dynamics.
• Develop statistical models for forecasting energy demand, supply and price fluctuations.
• Analyze market trends, regulatory changes and competition to identify risks and opportunities.
• Prepare reports, visualizations, and presentations for stakeholders.
• Perform economic analysis of energy projects including ROI calculations.

Skills

Data analysis

Python

R

SQL

Statistical modeling

Forecasting

Econometrics

Data visualization

Tableau

Power BI

Education

Bachelor's degree in Economics/Statistics/Mathematics/Engineering/Finance

Master's degree preferred

Tools

Python

R

SQL

Tableau

Power BI

Job description

Placements24 is seeking an Energetic Market Data Analyst in Oaxaca City to transform large energy data sets into actionable insights. You will forecast demand, analyze market dynamics, and support strategic decisions with robust models and clear visuals.

In a hybrid role, you will collaborate with engineering, finance, and strategy teams, using Python/R/SQL and BI tools to deliver data-driven recommendations and compelling presentations.