Designing, implementing, optimizing, deploying and maintaining statistical learning models (notably AI/ML models), based on business needs. Improve performance of pre-existing ones, managing their re-engineering and smooth transitioning.
Communicating with stakeholders to understand & refine the business needs. Derive data science goals, success metrics and tasks. Loop back learnings and feedback from stakeholders proactively to support the projects.
Defining, implementing and maintaining ETLs, that assemble large & complex datasets from heterogeneous data sources.
Performing Exploratory Data Analysis on datasets, derive actionable insights for stakeholders and improve data quality for further processing’s.
Building prototypes in controlled environments and data to perform quick iterations with stakeholders to improve, aiming for their productization.
Contributing to defining and implementing best practices in terms of infrastructure, deployment pipelines, CI/CD tools, code quality, unit tests.
Documenting processes, modeling steps, ETLs, reports, and tools, within the centralized dept documentation repository.
Skills Required
Machine Learning
Python
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