Senior Data Scientist (Forecasting)

TL;DR

Senior Data Scientist (Forecasting): Building, developing, and deploying predictive models for gas and power energy portfolios with an accent on time series analysis, demand forecasting, and portfolio sensitivity modeling. Focus on translating complex business challenges into analytical solutions, monitoring model performance, and collaborating with cross-functional stakeholders in risk and portfolio optimization.

Location: Based in Manchester (UK) or Kassel (Germany) with a hybrid working model.

Company

hirify.global is an international energy company owned by the Federal Government of Germany, managing the entire energy value chain to provide reliable gas and power solutions across Europe.

What you will do

• Build, develop, and deploy advanced forecasting models tailored to business requirements.
• Collaborate with stakeholders across risk, sales, portfolio optimization, and quant execution teams.
• Develop deep insights into demand patterns and perform sensitivity modeling for portfolios.
• Advance the framework for monitoring model accuracy and long-term performance.
• Maintain a continuous learning approach to ensure all analytical solutions remain at the cutting edge of industry standards.

Requirements

• High level proficiency in Python and SQL.
• Expertise in Machine Learning techniques and advanced analytical competencies.
• Strong organizational skills and ability to communicate complex data findings to diverse audiences.
• Proven experience in a data science role within the power or broader energy industry is highly desirable.
• Demonstrated success in the delivery of time series forecasting and analysis is highly desirable.

Culture & Benefits

• Competitive salary with bonus earning potential.
• Non-contributory pension scheme with 10% employer contribution.
• 25 days of annual holiday plus bank holidays and volunteering days.
• Comprehensive family medical and dental insurance.
• Flexible working environment with a hybrid model and options to buy or sell holidays.
• Opportunities for professional development through a blended learning approach.