Data Scientist — MLOps & Analytics Platform (all genders)

meteocontrol GmbH; Augsburg; Hybrid; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A renewable energy technology company in Bavaria is looking for a Data Scientist to develop MLOps pipelines and build data workflows. The candidate should have a Bachelor's or Master's degree in a relevant field and strong Python skills. The role involves collaboration across teams and mentoring junior developers, with a focus on creating data-driven solutions for performance analysis in renewable energy.

Leistungen

30 days of vacation, increasing to 35 days

Flexible working hours and home office model

Monthly SpenditCard worth €50

Employer subsidy for fitness and JobRad leasing

Qualifikationen

• 2–4 years of experience in Data Science, Analytics, or Machine Learning.
• Experience with data pipelines and workflow orchestration.
• Knowledge of time series analysis and forecasting.

Aufgaben

• Build and maintain MLOps pipelines for deployment and monitoring of ML models.
• Contribute to the development of a centralized analytics platform.
• Mentor junior team members and share knowledge.

Kenntnisse

Strong Python skills

Fluent in German and English

Experience with at least one ML framework (scikit-learn, TensorFlow, PyTorch)

Knowledge of SQL and relational databases

Ability to communicate complex technical concepts

Ausbildung

Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Physics, or a related field

Tools

Docker

Kubernetes

Cloud platforms (AWS)

Apache Airflow

Jobbeschreibung

Your profile:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Physics, or a related field
• 2–4 years of experience in Data Science, Analytics, or Machine Learning
• Strong Python skills and experience with at least one ML framework (scikit-learn, TensorFlow, PyTorch)
• Experience with data pipelines, workflow orchestration, and software development best practices (version control, testing, documentation)
• Knowledge of SQL and relational databases
• Ability to communicate complex technical concepts clearly
• Fluent in German and English

Nice to Have

• Experience with MLOps, model deployment, and CI/CD
• Knowledge of time series analysis, forecasting, and API development (FastAPI, Flask, or similar)
• Experience with Docker, Kubernetes, or cloud platforms (AWS)
• Background in energy, engineering, or technical projects
• Participation in open-source projects or technical communities

You can look forward to:

6 reasons to join meteocontrol (and more):

• Working for a better future: With us, you will create a better future for us and all generations after us.
• More flexibility: We know how important a good work-life balance is. That's why we offer flexible working hours and a home office model that adapts to your needs.
• Vacation that grows: Start with 30 days of vacation and your loyalty will be rewarded every two years with an additional day of vacation - up to 35 days for even more time off!
• Continuous learning & development: Your development is important to us - we support you in your career planning within the company with a wide range of offers.
• Money on top: In addition to your salary, you will receive a monthly SpenditCard worth €50 and a subsidy for the Deutschlandticket.
• Fitness: Train with our attractive employer subsidy at EGYM Wellpass, take part in our JobRad leasing program or power yourself up at our annual company run.

... You can find many more reasons on ourcareer website!

Your Contact Person

Camilla Geismar
Talent Acquisition Manager
[e-mail]

Your mission:

• Build and maintain MLOps pipelines for deployment, monitoring, and versioning of ML models
• Develop scalable, production-ready data workflows (e.g., with Apache Airflow, FastAPI)
• Contribute to the development of a centralized analytics platform for internal and external use
• Create modular components, APIs, and dashboards for analytics services
• Implement evaluation frameworks for forecasting and simulation quality
• Develop ML models for time series predictions in the renewable energy sector
• Implement automated anomaly and pattern detection
• Build data-driven solutions for performance analysis and component health assessment
• Collaborate with software development, product management, and other teams
• Mentor junior team members, share knowledge, and perform code reviews