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Tech Stack
Tools & technologiesAWSAzureBigQueryCloudGoogle Cloud PlatformGrafanaNumpyPandasPythonScikit-LearnSQL
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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.
Benefits
Comp & perks- 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Pythonpandasnumpyscikit-learnSQLSQLMeshBigQuerymachine learningdata pipelinesdata cleansing
Soft Skills
analytical mindsetteam-oriented mindsetagile mindsettroubleshootingcollaborationcommunication