Data Scientist - Retail

Roles & Responsibilities :

- Build predictive models, develop advanced algorithms that extract and classify information from large data sets quantify model performance.

- Analyze data, develop robust statistical algorithms/models that drive the product outputs.

- Apply various statistical techniques like, regression including logistic and OLS, clustering, optimization, classification and forecasting techniques in model development.

- Working experience in machine learning techniques (neural net, SVM, random forest etc.) is a plus point.

- Solve problems of large dimensionality in a computationally efficient and statistically effective manner.

- Based on business strategy and knowledge of emerging technologies, drive the architecture and design of the analytical platform.

- Evaluate emerging technologies that may contribute to our analytical platform.

- Identify and exploit new patterns in data using various techniques.

- Create meaningful analysis and modelling outputs that can be easily understood by clients and practically implemented to drive uplifts in performance

- Use a range of structured and unstructured data and tools (including transitional text, speech and digital analytics) as required to meet project objectives Maintain our analytical engines to ensure that day to day they deliver the functionality required by analysts and operations

- Research new data science opportunities in areas of prediction, - big data- and/or - real time- analysis to identify new opportunities and give recommendations for future solutions in metro.

- Ensure all work undergoes a thorough QA process and is 100% error free, resolving any issues or errors to give the best service to our countries/clients.

- Resolve complex data issues in creative and effective ways. High self-motivation for success in a fast-paced, dynamic environment.

Education:-

- Master- s/Bachelor's degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Applied Statistics, Mathematics, Physics, Engineering or related field.

Preferred Technical Skills

- Data Interpretation

- Analytical Technology

- R, Python, SAS Programming

- Quality Delivery

- Analytical Techniques

- Presentations

- Excel and Product Development

- Modelling and Statistics

- Coding