AVP - MIS Reporting Lead –SAS

We are seeking a highly experienced MIS Reporting Lead with deep domain expertise in the Credit Card and Lending industry and strong technical proficiency in SAS, Python, PySpark, and Tableau. The ideal candidate will be responsible for leading the design, development, and automation of management reporting solutions, and supporting strategic initiatives through insightful data analytics.

Key Responsibilities:

• Lead the end-to-end development and delivery of MIS reports and dashboards supporting US Personal Bank Credit card and Lending business across acquisition, early engagement, existing customer management, rewards, retention and attrition.
• Partner with business stakeholders to understand requirements and deliver actionable insights through automated reporting solutions.
• Interpret data to identify trends, patterns, and anomalies, and provide insights to stakeholders to support informed and strategic decision-making.
• Maintain and optimize existing SAS-based reporting processes while leading the migration to Python/PySpark on Big Data platforms.
• Design and build interactive dashboards in Tableau for senior leadership and regulatory reporting.
• Build and implement an automated reporting control framework to ensure accuracy across the entire reporting life cycle. 
• Collaborate with Data Engineering and IT teams to leverage data lakes and enterprise data platforms.
• Mentor junior analysts and contribute to knowledge sharing across teams.
• Support ad-hoc analysis and audits with quick turnaround and attention to data integrity.

Qualifications:

• Master’s degree in Computer Science, Statistics, Finance, or related field.
• Proficiency in SAS (Certification).
• 8+ years of experience in MIS reporting, data analytics, or BI teams in the Banking/Financial Services.
• Advanced skills in Python and PySpark, particularly in big data environments (e.g., Hadoop, Hive, Databricks).
• Expertise in Tableau for dashboard design, develop and data storytelling.
• Experience in managing team of data analysts (10-15)
• Excellent communication and presentation skills.