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Dennis ReimerDR

Dennis Reimer

Data Scientist

300 €/Tag
München, DE
0-2 Jahre

Durchschnittliche Reaktionszeit: 1h

Über Dennis

I am a Data Scientist with a strong interest in Machine Learning and AI Engineering, with hands-on experience across a wide range of data-driven use cases, including forecasting, data engineering, and applied analytics. I enjoy working on practical problems and building solutions end-to-end, from data processing to model development and deployment.

I am particularly interested in opportunities in ML and AI Engineering, as well as forecasting-related projects, where I can further deepen my expertise and contribute to impactful solutions. At the same time, I am actively looking to take on projects outside of a full-time role, especially as I am aiming to secure my first freelance engagement and gain more experience in client-driven environments.

I am motivated by continuous learning, new challenges, and the opportunity to work on diverse problem domains. I am open to entry-level freelance projects and collaborations, and I am eager to bring a structured, analytical, and hands-on approach to new tasks and ideas.
  • Deutsch

    Muttersprachlich oder zweisprachig

  • Englisch

    Verhandlungssicher

  • Russisch

    Grundkenntnisse

Vor Ort möglich
München (bis zu 50 km)

Projekt- und Berufserfahrung

  • Tchibo
    Data Science In.
    Juni 2025 - Januar 2026 (7 Monate)
    • • Entwicklung von End-to-End ML-Pipelines für Demand & Cost/Margin Forecasting
    • • Automatisiertes Training & Inference via Docker & CI/CD
    • • Monitoring und Modellversionierung im produktionsnahen Setup
    Machine learning Forecasting Data Analytics DevOps Google Cloud Platform (GCP)
  • Koenigs Investment SIA
    Data Engineer/Analyst
    Januar 2025 - April 2026 (1 Jahr und 3 Monate)
    - Built and maintained data pipelines for processing logistics and supply chain data (ETL/ELT)
    - Designed and optimized databases (SQL, data modeling)
    - Integrated data from multiple sources (e.g., SAP, APIs, internal systems)
    - Automated reporting and data workflows
    - Ensured data quality and monitored data processes
    - Collaborated with business teams to support data-driven decisions
    Google Cloud Platform (GCP) Data Engineering Forecasting Internationales Projektmanagement Data Pipelines

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