Senterprise - IT Experts Delivered

Senior Data Scientist

Senterprise - IT Experts Delivered

contract

Posted on:

Origin:  • 🇸🇪 Sweden

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Salary

💰 SEK 1,050 - SEK 1,100 per hour

Job Level

Senior

Tech Stack

BigQueryCloudGoogle Cloud PlatformKeras.NETNumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

  • Konsultuppdrag som Senior Data Scientist / Data Engineer i Stockholm (hybrid)
  • Bygga, driftsätta och operationalisera ML/LLM-lösningar och pipelines på Google Cloud Platform (Vertex AI, BigQuery, Dataflow, Cloud Functions, Cloud Run)
  • Utveckla och debugga maskininlärningspipelines i Python
  • Sätta upp och hantera utvecklingsmiljöer, inklusive Jupyter Notebooks, för effektiv modellutveckling och experimentering
  • Ansvara för kunskapsöverföring: förklara best practices, arkitekturval och skalbara AI-setup på GCP
  • Implementera Responsible AI-principer: modellövervakning, datastyrning, fairness och explainability
  • Samarbeta med team, stödja delade mål och främja lärande
  • Delta i designbeslut kring CI/CD och versionshantering för ML-lösningar

Requirements

  • Proven experience with Google Cloud Platform (GCP), including Vertex AI, BigQuery, Dataflow, Cloud Functions, and Cloud Run
  • Strong Python programming skills, including building and debugging machine learning pipelines
  • Problem-solving mindset: strong analytical skills and ability to take ownership and drive solutions independently
  • Excellent communication abilities and fluency in English
  • Skilled in knowledge transfer: able to explain best practices, architecture choices, and scalable AI setups on GCP
  • Team-oriented mindset: supports shared goals, takes ownership, and fosters learning
  • Proficient in setting up and managing development environments, including Jupyter Notebooks
  • Deep practical knowledge of ML frameworks: scikit-learn, TensorFlow, PyTorch, Keras
  • Experience with LLMs and Generative AI: Gemini, LangChain, Hugging Face
  • Data processing: Pandas, NumPy
  • Visualization: Matplotlib, Seaborn
  • Responsible AI practices: model monitoring, data governance, fairness and explainability
  • Version control & collaboration tools: Git, GitHub/GitLab, CI/CD workflows
  • Nice to have: Experience with MLOps principles and tools
  • Nice to have: Experience with Microsoft Power Platform
  • Nice to have: Exposure to DevOps practices and infrastructure-as-code
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