ML Quant/Data Scientist: Energy Markets Forecasting

eFinancialCareers; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

We are partnering with a leading energy trading organisation to recruit a talented Machine Learning Quant/Data Scientist to join its Analytics team.

You will develop forecasting models for power, gas and other energy markets, applying machine learning and statistics to predict prices and demand. You’ll analyse large datasets from market and weather sources and provide insights to support Front Office trading decisions, working with Trading, Quant Analytics and Technology teams.

Qualifications

• PhD in Computer Science, ML, Data Science, or a highly quantitative field.
• 1–3 years' commercial experience as a Data Scientist, ML Engineer, or Quantitative Analyst.
• Experience forecasting/predictive modelling using machine learning techniques.
• Strong Python programming with Pandas, NumPy and Scikit-learn.

Responsibilities

• Develop and improve forecasting models for energy markets (power and gas).
• Apply ML and statistics to predict prices, demand and other market variables.
• Analyse large datasets from market, weather, generation and trading sources to identify predictive patterns.

Skills

Python

Pandas

NumPy

Scikit-learn

Time-series

Predictive modelling

Statistics

Education

PhD in CS/ML/DS

Tools

Pandas

NumPy

Scikit-learn

Job description

We are partnering with a leading energy trading organisation to recruit a talented Machine Learning Quant/Data Scientist to join its Analytics team.

You will develop forecasting models for power, gas and other energy markets, applying machine learning and statistics to predict prices and demand. You’ll analyse large datasets from market and weather sources and provide insights to support Front Office trading decisions, working with Trading, Quant Analytics and Technology teams.