We are looking for an experienced Data Scientist / Advanced Analytics professional with strong expertise in statistical modelling, predictive analytics, experimentation, and Azure data platforms. The ideal candidate will be responsible for developing analytical models, translating business problems into data-driven solutions, and delivering insights that drive measurable business impact.
The role requires strong hands-on expertise in Python, SQL, statistical modelling, machine learning, and Azure, along with the ability to work closely with business and senior stakeholders.
- Build, validate, and deploy predictive, statistical, and time-series models using Python and R.
- feature engineering, model selection, cross-validation, and hyperparameter tuning techniques.
- Develop models using regression, tree-based algorithms, clustering, and forecasting techniques.
- Interpret model results and translate them into actionable business insights.
- Document model methodologies, assumptions, validation results, and performance metrics.
- Design and analyse A/B tests and controlled experiments.
- Define appropriate metrics, sample sizes, statistical power, and validation approaches.
- causal inference methodologies where controlled experimentation is not feasible.
- Evaluate experiment results and provide clear recommendations to stakeholders.
- Develop complex SQL queries for large-scale analytical datasets using Azure SQL and Azure Synapse.
- Build and maintain data pipelines using Azure Data Factory and Databricks.
- Leverage Azure Machine Learning for experiment tracking, model management, and deployment.
- best practices in data modelling, performance optimization, version control, and production-grade analytics workflows.
- Translate complex business problems into structured analytical approaches.
- Manage analytics projects from problem definition through modelling, validation, and delivery.
- Present analytical findings and recommendations to senior business and technical stakeholders.
- Proactively identify trends, patterns, and opportunities where advanced analytics can create business value.
- Mentor junior analysts and data scientists.
- Conduct code and model reviews.
- Promote best practices in model governance, testing, documentation, reproducibility, and analytical standards.
- Strong experience in predictive modelling, statistical modelling, and machine learning.
- Hands-on experience with:
- Regression
- Tree-based models
- Clustering
- Time-series forecasting
- Strong understanding of statistical testing, A/B testing, experimental design, and causal inference.
- Strong proficiency in Python, including Pandas and Scikit-learn.
- Strong SQL skills with experience handling large-scale datasets.
- Working knowledge of R is preferred.
- Hands-on experience with Azure Synapse, Azure Data Factory, and Azure Machine Learning.
- Familiarity with Databricks, dbt, Git, and production-grade analytical workflows.
- Strong communication and stakeholder-management skills.
- 6–10 years of relevant experience in Data Science, Advanced Analytics, Quantitative Analytics, or a similar role.
- Proven track record of developing models that have delivered measurable business impact.
- Experience working with large-scale cloud data environments.
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or another quantitative discipline, or equivalent practical experience.
