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Mid-level ML role, metro location, and generalist ML/MLOps skillset produce moderate competition.
ML/AI and MLOps skills are transferable across industries, though financial-services experience is preferred.
Explicit 5.1–7 years, advanced degree preference, and specific ML/MLOps tooling make screening strict.
Improve AI models by managing data collection, labeling, curation, structuring, and feature engineering.
Deploy and automate AI applications using tools like CI/CD pipelines, AirFlow, and MlFlow, including effective model monitoring for data drift.
Promote and implement new technologies and best practices for testing and automation improvements.
Master’s degree in statistics, computer science, engineering, or related quantitative field (PhD is a plus).
At least 3 years of experience in data science, preferably in the financial sector.
Strong hands-on skills in SQL, Pandas, Hadoop/Spark, web scraping, and extensive Python programming experience.
Location requirement: Chennai.
Experience working in Agile Scrum teams within dynamic, multicultural environments.
Ability to communicate fluently in English with business stakeholders and data scientists.
Demonstrated analytical approach combining code and data to build and improve AI solutions, with a customer-oriented mindset.