Data Analyst

Data Analyst / Analytics Engineer

Location: Solna, Stockholm, Sweden

Start Date: 1st October 2026

End Date: 31st March 2027

Work Style: Monday - Friday / Hybrid, 40 Hours Weekly

Role Objective

• Support the Power Forecasts product team in producing local-grid and regional-grid forecasts for housing, transport electrification, industry, and commercial premises.
• Maintain and improve a data-driven, automated forecasting workflow centred on Python scripts.
• Produce reliable forecasts and insights for network dimensioning, network-development planning, investment decisions, and customer dialogue.
• Enhance the quality, efficiency, and analytical value of forecasting, data-modelling, and reporting processes.

Key Responsibilities

• Automate forecasting activities previously completed manually using Python within a Databricks environment.
• Analyse customer and time-series data to develop improved forecasting methodologies.
• Build new Power BI reports and enhance existing reports through data modelling, calculations, and additional functionality.
• Update power forecasts for specific geographical areas and generate quantitative and qualitative insights.
• Assess data availability, combine information from multiple sources, and ensure data quality and reliability.
• Communicate analytical findings clearly to internal and external stakeholders.

Tasks

• Develop clear and efficient Python code to automate forecast preparation and processing.
• Conduct both defined analyses and exploratory investigations into customer and time-series data.
• Collaborate with colleagues from other disciplines to assess potential changes to forecasting methodology.
• Develop Power BI data models, calculations, visualisations, and report functionality.
• Gather, validate, process, and quality-assure input data used in power forecasts.
• Liaise with municipalities and local-grid customers when updating forecasts for specific areas.
• Prepare and present forecast results, insights, and supporting materials to relevant stakeholders.
• Contribute to the continuous development of automated and data-driven ways of working within the product team.

Deliverables

• Automated and maintainable forecasting workflows within Databricks.
• Updated local-grid and regional-grid power forecasts.
• Customer-data and time-series analyses supporting methodology development.
• Accurate and usable Power BI reports, data models, and calculations.
• Quality-assured datasets, analytical insights, and stakeholder presentation materials.

Decision Authority / Responsibility

• Own assigned analysis, automation, reporting, and forecast-update activities through to completion.
• Recommend improvements to forecasting methodologies, data models, and automated workflows based on evidence and analysis.
• Identify and escalate material data-quality, reliability, and methodological risks.
• Ensure analytical results and reporting outputs are clear, reliable, and suitable for stakeholder decision-making.

Requirements

• Several years of experience analysing large datasets, particularly customer data and time series, including data manipulation, modelling, and presentation of results to stakeholders.
• Several years of experience developing efficient, understandable code using Python or a comparable programming language.
• Professional experience in the electricity-network sector or other relevant energy-industry experience.
• Professional experience with data-visualisation tools such as Power BI.
• Strong analytical ability and advanced problem-solving skills.
• Able to communicate complex findings and messages clearly to different stakeholders.
• Relevant academic degree, such as an MSc in Engineering in Applied Physics, Energy Systems, Electrical Power Engineering, or another relevant technical discipline.
• Previous experience in insight generation and/or forecasting is advantageous.
• Experience working in an Agile Scrum team or equivalent environment is advantageous.
• Experience with artificial intelligence and machine learning is advantageous.
• Experience with SQL or an equivalent query language is advantageous.