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Tier-1 bank, mid-level analytics role in metro with common skillset drives very high competition.
Core Python/PySpark/SQL analytics skills are transferable, though banking/credit experience increases domain specificity.
Explicit years plus mandatory Python/PySpark/SQL skills and banking compliance make shortlisting highly strict.
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Gather and analyze operational data from multiple cross-functional stakeholders to evaluate past business performance and identify actionable patterns and trends.
Translate data into consumer or customer behavioral insights to influence targeting, segmentation strategies, and business decision-making with clear communication to senior leaders and partners.
Continuously improve data processes, tools, and decision strategies while managing risk and compliance to protect the firm, clients, and assets.
3-5 years of relevant experience in a quantitative field, preferably Financial/Credit Card industry.
Hands-on experience with Python, PySpark, and SQL; Tableau experience is a plus.
Masters or University degree or equivalent experience.
Not explicitly mentioned: notice period or location requirements.
Experienced in applying advanced analytics and problem-solving skills to business questions through data-driven solutions.
Able to work effectively in a matrix environment with strong communication and organizational skills.
Comfortable handling business risk and compliance considerations when implementing data strategies.