Responsible for designing, developing, and deploying advanced analytics and machine learning solutions
Translate business problems into data science use cases and define appropriate analytical approaches
Design, build, and validate statistical and ML models (e.g., forecasting, classification, optimization, recommendation)
Develop and maintain production-grade models with appropriate monitoring, retraining, and governance
Explore and design solutions using Large Language Models (LLMs) and other GenAI capabilities
Engage with business stakeholders to understand objectives, define success criteria, and prioritize use cases based on value and feasibility
Lead or co-lead end-to-end data science projects: from ideation, scoping and estimation through development, testing, deployment, and post-go-live monitoring

Master's/bachelor's degree in data science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
5–7 years of hands-on experience in data science / advanced analytics roles
Strong proficiency in Python and SQL
Solid, practical experience with Azure Databricks (Spark-based data processing, notebooks, workflows/jobs)
Experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, or similar
Exposure to Large Language Models (LLMs) and NLP techniques, ideally using platforms such as Azure OpenAI, OpenAI, or Hugging Face for building text analytics or conversational solutions
Experience on a major cloud platform (preferably Microsoft Azure) and familiarity with data/ML services (e.g., Azure Data Lake, Synapse, Data Factory, Azure Machine Learning)
Proven track record of delivering and deploying ML solutions into production with measurable business outcomes.

Data Scientist

Key skills