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Here is a short description of the Senior Data Scientist / Machine Learning Engineer (ML Productionization) role based on the provided job description and screening criteria:
Role Overview: A centralized ML team position embedded to support the Customer Intelligence (CBI) initiative, focusing on taking machine learning models from prototype into scalable production environments.
Experience Level: Requires a minimum of 8 years of professional experience (9+ preferred) alongside a Master's or PhD degree in a quantitative discipline.
Core Technical Stack: Strong production-grade Python expertise, Databricks, Azure, SQL, parallel processing, and machine learning pipeline development/productionization.
Top Must-Haves: MS/PhD in a quantitative field, expert-level Python production coding (modularization, testing, performance optimization), and hands-on ML pipeline orchestration, deployment, and monitoring.
Key Responsibilities: Full technical ownership of productionizing ML pipelines, code refactoring/optimization, containerization, and collaborating closely with Data Scientists, Data Engineers, and business stakeholders.
Synergyassure is dedicated to provide comprehensive technology solutions and guidance to businesses across various industries. With a wealth of expertise and a team of highly skilled professionals, we empower organizations to navigate the rapidly evolving digital landscape and leverage technology for enhanced productivity, efficiency, and growth.
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