Job Description
Responsibilities:
- Design, build, and optimize scalable predictive models and machine learning algorithms to solve complex business challenges.
- Architect and maintain robust data pipelines and feature sets, ensuring data quality, consistency, and integrity across training and inference layers.
- Partner with Data Engineers, Product Managers, and Backend Teams to integrate ML models seamlessly into core application APIs.
- Conduct rigorous peer code reviews for data science workflows, championing production-grade Python design patterns and linting standards.
- Translate highly technical metrics (Precision, Recall, ROC-AUC, RMSE) into clear business outcomes and executive-level recommendations.
What we are looking for:
- 5+ years of professional experience as a Data Scientist, with expert-level mastery of the Python data ecosystem (Pandas, NumPy, SciPy, Scikit-Learn).
- Deep theoretical and practical knowledge of supervised and unsupervised learning, regression, classification, clustering, and time-series forecasting.
- Proven track record of moving models out of Jupyter Notebooks and into production environments using containerization (Docker) and microservice design.
- Strong proficiency in writing complex, optimized SQL queries and experience handling large-scale data using distributed computing frameworks like PySpark or Ray.
- Experience with machine learning lifecycle tools (such as MLflow, DVC, or Weights & Biases) for model tracking, versioning, and feature store management.
- Hands-on experience leveraging cloud data infrastructure (AWS, GCP, or Azure) and managed ML services (e.g., SageMaker or Vertex AI).
- Time zone: CET (+/- 3 hours). We are unable to consider applications from candidates in other time zones.
Nice-to-have:
- Deep Learning experience using PyTorch or TensorFlow/Keras.
- Experience with NLP frameworks (Hugging Face, spaCy) or deploying LLM-based pipelines (LangChain, vector databases).
- Familiarity with orchestration tools like Apache Airflow or Prefect.
- Strong background in experimental design, A/B testing methodologies, and statistical significance validation.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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