Energy Forecasting Quantitative Analyst | ML & Python

Drax; Felixstowe; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Discretionary bonus

Private healthcare

SAYE (Sharesave)

Personal accident cover

Group pension 10%

25 days holiday + bank holidays

Professional body membership

Job summary

Drax is recruiting a Quantitative Analyst to develop and improve forecasting models across import and export portfolios. You will apply statistical, machine learning and optimisation techniques to boost forecast accuracy and commercial value.

You will design automated reporting and dashboards using Python, SQL and Power BI to support portfolio monitoring and decision-making, and provide time-critical analyses to several business areas.

Qualifications

• Strong quantitative and analytical abilities with a numerate degree.
• Experience with forecasting models and energy markets preferred.
• Proficiency in Python and SQL for data analysis.

Responsibilities

• Develop, maintain and enhance forecasting models for import/export portfolios.
• Research and implement statistical, ML, and optimisation techniques to boost accuracy and value.
• Lead code reviews and maintain high-quality analytics practices.
• Design dashboards and automated reporting using Python, SQL and Power BI.
• Provide ad-hoc quantitative analysis to support multiple business areas.
• Contribute to new forecasting capabilities across demand, generation, weather and pricing.

Skills

Python

SQL

Forecasting

Machine Learning

Statistics

Energy markets

Education

Math/Stats degree

Tools

Power BI

Job description

Drax is recruiting a Quantitative Analyst to develop and improve forecasting models across import and export portfolios. You will apply statistical, machine learning and optimisation techniques to boost forecast accuracy and commercial value.

You will design automated reporting and dashboards using Python, SQL and Power BI to support portfolio monitoring and decision-making, and provide time-critical analyses to several business areas.