- Apply and/or develop statistical modeling techniques (such as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques.
- Synthesize problems into data questions.
- Convert data into practical insights.
- Analyze and investigate data quality for identified data and communicate it Product Owner, Business Analyst, and other relevant stakeholders.
- Collect Data, explore it, and perform analysis to extract information suitable to the business need. Identify gaps in the data, aggregate data as per business need. Design & perform Data Analysis, Data Validation, Data Transformation, Feature Extraction.
- Decide approach for addressing business needs with Data & analytics. Understand end user needs and work accordingly with identifying recent features in the data.
- Develop Data Science and Engineering Infrastructure &Tools.;
- Derive key metrics suitable for the use-case and present the analysis to key stakeholder.