Data Scientist (Azure), 5+ years experience

General

We are looking for Data Scientists with strong Azure experience to join our client’s team. The role focuses on developing machine learning and statistical modelling solutions using Azure cloud services, Python, SQL, and modern data science practices.

 

Responsibilities/Activities

• Analyse structured and unstructured datasets to identify patterns, trends, and actionable business insights
• Translate business problems into data science use cases, analytical approaches, and machine learning solutions
• Design, develop, validate, and improve machine learning models using Python and relevant ML libraries
• Perform data preparation, feature engineering, model training, hyperparameter tuning, and model evaluation
• Work with data stored in Azure-native platforms such as Azure Data Lake Storage, Azure Databricks, Delta Lake, and Synapse Analytics
• Use Azure Machine Learning and MLflow for experiment tracking, model versioning, reproducible workflows, and model lifecycle support
• Collaborate with Data Engineers, ML Engineers, and DevOps teams to support deployment, monitoring, and retraining of ML models in production
• Apply statistical modelling, probability, hypothesis testing, experimentation, and model interpretability techniques to support business decision-making
• Use Python and SQL for data exploration, feature development, model training, and analysis
• Create clear visualizations and reports using tools such as Power BI, Plotly, or similar
• Communicate findings, model results, limitations, and recommendations to both technical and non-technical stakeholders
• Contribute to responsible AI practices, including explainability, fairness, data privacy, and governance considerations
• Explore generative AI and Azure OpenAI use cases where relevant to business needs

Requirements

Technical

• At least 5 years of experience in data science roles within a commercial environment
• Experience with the full data science lifecycle: data exploration, feature engineering, model development, validation, evaluation, and improvement
• Good understanding of statistical modelling, probability, hypothesis testing, experimentation, and model evaluation techniques
• Advanced proficiency in Python for ML/AI and SQL for data processing, analysis, and feature engineering
• Practical experience with machine learning frameworks and libraries (Pandas, NumPy, scikit-learn, PySpark ML, TensorFlow, PyTorch, Keras)
• Experience with Azure services relevant to data science (Azure Machine Learning, Azure Databricks, Azure Data Lake Storage, Delta Lake, Azure Synapse Analytics)
• Experience working with Databricks, PySpark, and distributed data processing for large datasets
• Experience with data visualization and reporting tools such as Power BI, Plotly, Matplotlib, Seaborn, or similar
• Experience using MLflow, experiment tracking, model registries, model versioning, and reproducible ML workflows
• Understanding of MLOps concepts, including model deployment, monitoring, retraining, CI/CD, and collaboration with engineering or DevOps teams.
• Ability to assess and improve model performance, scalability, interpretability, and business relevance
• Ability to translate business requirements into analytical and machine learning solutions

Education

• University degree in Mathematics, Statistics, Data Science, or another related field

Others

• Good level of English (oral and written)
• Strong analytical and problem-solving skills
• Attention to detail and ability to work with complex data and production constraints
• Critical thinking and business-oriented mindset

Nice to have requirements

• Experience designing or implementing generative AI or Azure OpenAI-based solutions
• Knowledge of responsible AI, model explainability, data privacy, governance, and regulatory requirements
• Experience with Azure DevOps, GitHub Actions, CI/CD pipelines, or containerization
• Experience with Azure Functions or other Azure services used for solution integration