Reporting Insights and GenAI-Assistant Vice President

We are seeking an experienced and strategic AVP for our Reporting Insights and GenAI Team. The ideal candidate will be responsible for driving the development and implementation of analytical solutions to support key business objectives for Banking Operations & Analytics as part of COO (Chief Operating Office). This role requires a strong analyst with a proven track record of delivering impactful insights and fostering a data-driven culture. Roles and Responsibilities: The Reporting Insights and GenAI AVP (Banking Operations & Analytics) accomplishes results by contributing significantly to the bank's success by focusing on improving efficiency, accuracy, and insights through data and process optimization. The responsibilities involve a blend of data analysis, report generation, and the development of automated solutions. Data Collection and Analysis: Gathering data from various sources, cleaning it, and analyzing it to identify trends, patterns, and insights relevant to business operations. MIS and Reporting: Designing, developing, and maintaining regular and ad-hoc Management Information Systems (MIS) and reports for different stakeholders. These reports often present key performance indicators (KPIs), operational metrics, and financial data in an understandable format. Automation Development: Identifying manual, repetitive tasks and processes within the organization and developing automated solutions to streamline them. This can involve scripting, using automation tools/technologies like SQL, SAS, Python, PySpark, Tableau etc. Process Improvement: Analyzing existing workflows to pinpoint inefficiencies and recommend improvements, often leveraging automation to achieve these. Dashboard Creation: Developing interactive dashboards using reporting tools (e.g., Tableau, Python, Power BI) to provide real-time visibility into performance and trends. Applied AI and GenAI Integration: Leading the exploration, development, and integration of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) solutions. This includes leveraging Large Language Models (LLMs), Natural Language Processing (NLP), and predictive analytics to enhance data-driven decision-making and automate complex analytical processes. Stakeholder Communication: Presenting findings and recommendations to various departments and management, explaining complex data in a clear and concise manner. System Maintenance: Ensuring the accuracy and reliability of reporting systems and automation tools, troubleshooting issues, and performing regular updates. Documentation: Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include Process Automation / Optimization and data visualization techniques. Data Governance and Quality: Contributing to efforts to maintain data quality, consistency, and adherence to data governance policies. Data Handling: Work with large, complex and unstructured data to evaluate, recommend, and support the implementation of business strategies Core Competencies: Data Analysis & Insight Extraction: Proficiently applying analytical techniques to complex datasets to fetch meaningful, actionable insights that address business questions and drive decision. Data Manipulation & Querying: Expert ability to query and manipulate data from various data sources (using SQL/Python/R), ensuring data quality and readiness for analysis and reporting. Reporting & Visualization Tools: Expertise in using reporting & visualization platforms (e.g., Tableau, Power BI, Qlik Sense, MicroStrategy) to design, develop, and maintain dynamic dashboards and reports that clearly communicate performance and insights. This includes a strong focus on MIS and executive-level reporting. Automation Technologies & Scripting: Strong capability in identifying automation opportunities, developing and implementing automated solutions using automation tools and scripting languages, and optimizing