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 current 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.