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Tier-1 brand, metro location, and broad analytics/ML skillset make competition high.
Core ML, NLP and analytics skills transferable, but marketing and financial domain knowledge moderately matters.
Explicit 5-8 years plus mandatory ML, NLP, Python, SQL and domain experience increases strictness.
Lead multiple analytics projects focused on client life cycle stages such as acquisition, engagement, retention, and client experience for the Treasury & Trade Services business.
Develop predictive models and data-driven insights using multiple analytical methodologies, big data tools, and machine learning algorithms to support sales, marketing strategy optimization, pricing, and cross-sell initiatives.
Work with diverse data sources including client profiles, transaction data, digital data, and unstructured data like call transcripts to deliver actionable insights to business and functional stakeholders.
Bachelor’s degree with 5-8 years or Master’s degree with 4-8 years in data analytics; PhD holders may also qualify.
Mandatory experience in marketing analytics with focus on sales/marketing strategy optimization, pricing optimization, client experience, cross-sell, and retention.
Proficiency in Python or R, SQL, and Hive with experience in predictive modeling using machine learning and analysis of unstructured data via NLP or text mining.
Work Experience Required: 4-8 years in data analytics, with specific marketing analytics exposure.
Experienced in applying diverse analytical methods such as hypothesis testing, segmentation, time series forecasting, and test vs. control comparisons in a business context.
Capable of handling big data environments and combining structured and unstructured data sources for comprehensive insights.
Skilled in translating complex business problems into analytical solutions and communicating outcomes effectively to management and stakeholders.