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Strong Tier-1 brand, metro location, and visible data scientist manager role drive high competition.
Technical ML and data engineering skills transfer across industries, but payments/product domain knowledge increases sensitivity.
Mandatory ML production experience and specific tech stack (Python, Spark, Hadoop, SQL) increase filtering.
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Design, develop, and maintain advanced analytics and machine learning solutions driving product optimization, growth, and sales enablement.
Lead end-to-end design, validation, monitoring, and continuous improvement of complex predictive models ensuring scalability and performance.
Translate complex data and model results into actionable insights for senior stakeholders and implement robust data pipelines handling large-scale datasets.
Strong academic background or equivalent experience in Computer Science, Data Science, Technology, Mathematics, or Statistics.
Proficiency in Python, Spark, Hadoop platforms (Hive, Impala, Airflow, NiFi), and SQL.
Experience leading machine learning model development and deployment with cross-functional teams.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and scaling machine learning and data science solutions in a fast-paced, deadline-driven environment.
Skilled at translating complex analytics into clear business insights and communicating effectively with diverse stakeholders.
Familiar with emerging AI/ML technologies and responsible AI frameworks, capable of driving innovation and compliance.