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Tier-1 brand, mid-level data scientist in metro with broad ML and analytics skill requirements.
Core ML and analytics skills transferable, but banking domain knowledge and regulatory context increases specificity.
No explicit years but requires ML, big-data and ML-DevOps skills, raising moderate strictness.
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Develop and deploy advanced analytic systems using machine learning, text mining, and statistical analysis to support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research.
Handle complex data challenges including very large databases, multi-structured, and big data environments.
Manage or contribute to machine learning DevOps life cycle and agile practices, potentially managing associates and leading teams to meet business outcomes.
Minimum education: High School Diploma / GED / Secondary School or equivalent.
Experience working on machine learning, statistical analysis, or related advanced analytics projects.
Familiarity with machine learning DevOps life cycle and agile practices required.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and deploying sophisticated analytic models in large and complex data environments.
Comfortable managing or coaching associates and leading team processes focused on business impact and continuous improvement.
Skilled in communicating complex technical topics clearly and aligning analytics efforts with business goals and risk management.