Data Scientist
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Requirements
- Education: Master’s or Ph.D. in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related discipline; equivalent professional experience will also be considered.
- Experience: 10+ years of hands-on experience in data science, machine learning, advanced analytics, or a closely related field.
- Technical Skills: Advanced proficiency in Python and SQL, with strong hands-on expertise in Azure Databricks and PySpark.
- Machine Learning: Extensive knowledge of machine learning methods, including anomaly detection, classification, clustering, explainable AI, and risk-scoring models applied to large-scale datasets.
- Databricks Platform: Proven experience with key Databricks capabilities, including MLflow, Delta Lake, Unity Catalog, and Databricks Workflows.
- Engineering & MLOps: Strong understanding of software engineering and MLOps practices, including Git, automated testing, CI/CD pipelines, model deployment, and lifecycle management.
- Ways of Working: Demonstrated experience delivering solutions within Agile development environments.
- Industry Experience: Background in healthcare, insurance, fraud detection, or the public sector would be highly advantageous.
Requirements
Technical Skills Required Expertise in statistics and machine learning 7 to 10 years of experience in data science, ideally in the healthcare sector Knowledge of regulatory standards (FDA, GMP, ISO) Excellent written and spoken English Ability to write detailed technical documentation in English Proficiency in R and/or Python Expected Soft Skills Rigor, autonomy, and strong organizational skills Ability to work in a multicultural and project-based environment Strong interpersonal skills: listening, teaching, simplification, synthesis Service-oriented and scientifically driven mindset Ability to lead and collaborate remotely Flexibility regarding project changes and scheduling constraints Effective in reporting and meeting facilitation
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