Working Student Data Science Forecasting (m/f/d)

As a Werkstudent or Intern in Data Science Forecasting, you will join our Team to help shape the future of decentralized Energy Management Systems (EMS). Your core mission will be supporting the development, training, and testing of our time-series forecasting models (PV generation, household load, heat pump consumption, and EV charging).

This role offers a unique learning ground: you will get hands-on experience working on data and ML pipelines and projects running in live production. You will join us during a period of rapid innovation, gaining the opportunity to actively contribute to our agentic AI workflows aimed at accelerating engineering productivity. This position is ideal for a student who wants to bridge the gap between academic data science theory and real-world, cloud-scale clean energy operations.

Key Responsibilities

• Time Series & ML Engineering: Support the team in building, improving, and retraining machine learning forecasting models 

• Production Operations: Actively assist in monitoring, updating, and troubleshooting forecasting models and pipelines operating in production environments

• Data Pipelines & Cleansing: Help build and maintain robust data transformation pipelines using SQLMesh and BigQuery to pre-process large streams of data

• Simulation & Validation: Use our internal simulation framework to backtest forecast models and analyze how forecast errors directly impact our high-level EMS optimization yield

• Agentic AI & Workflow Automation: Assist in writing, structuring, and testing behaviors for autonomous AI agents to help automate workflows

• Documentation & Team Sync: Help maintain clean, clear technical documentation in Notion and collaborate with Optimization and Data Engineers during sprint cycles

• Current Studies: Enrolled in a Bachelor’s or Master’s program in Data Science, Computer Science, Statistics, Mathematics, Physics, or an equivalent quantitative field

• Python Foundations: Solid coding skills in Python and familiarity with core data science libraries (pandas, numpy, scikit-learn)

• ML Domain Knowledge: Solid theoretical understanding of machine learning principles, statistical analysis, model architectures (e.g., regression, tree-based ensembles), and key evaluation metrics

• Analytical Mindset: Enthusiastic about troubleshooting data quality bugs and validating model outcomes using quantitative metrics

• Team & Agile Mindset: You have a team-oriented mindset, enjoy working in agile environments (such as sprints), and deeply value close, transparent collaboration with your teammates

• Domain Interest: A genuine interest in renewable energy, battery storage systems, smart grids, or electricity markets

Bonus points for:

• First touchpoints working with cloud-based infrastructure (e.g. GCP, AWS, Azure), especially containerized workflows and data warehouse solutions

• SQL Literacy: Understanding of relational databases and confidence writing SQL queries for data extraction, manipulation, and aggregation.

• hands-on experience using generative AI tools, prompt engineering, or configuring AI coding assistants 

• Initial experience with data pipeline tools like SQLMesh or dbt.

• Basic understanding of visualization tools like Grafana or Looker.

• You are part of an international, dynamic, and highly motivated team of people who have proven to make things happen
• With your work, you accelerate the "energy transition" and hence have a direct impact on our climate
• Work with and learn from other super-smart colleagues
• You will enjoy direct contact with core decision-makers
• You will enjoy the best chances of entering in one of Europe’s most thriving scaleups
• You work remotely (Germany-wide), with offices in Hamburg, Berlin or Munich
• Create a healthy balance alongside your work and enjoy all the benefits of the EGYM Wellpass
• Benefits and discounts are yours with Futurebens