About

Anwar Jameel is an Assistant Vice President at Bank of America Merrill Lynch with over 6 years of professional experience in software development, data engineering, and business analytics. He is currently empowering the Global Wealth and Investment Management business with valuable insights that are consumed by Financial Advisors and Client Associates daily. Anwar is actively helping the Market Executives in driving meaningful conversations with their clients and is involved in learning from the market executives and extrapolates the performance of insights to gauge the business growth. Under his leadership, thousands of clients have benefitted from various Merrill Lynch products such as Retirement benefits, Healthcare benefits, Cares Act, Mortgages, Wealth Management, etc. Anwar is a good mentor and has trained onshore and offshore developers to support data product development and BI reporting. Anwar's technical expertise includes Hadoop, Big Data, Data Engineering, Data Warehouse, Software Engineer, Python, Java, and Apache Hive. He has worked on developing and maintaining applications for Global Wealth Management Advisory and has designed and built software solutions using Java, Python, and Shell Scripting on the Hadoop platform leveraging Hive and Impala. Anwar has a Master's degree in Computer Science from Rutgers University and a Bachelor of Engineering in Computer Science from Manipal Institute of Technology. He is currently pursuing an Executive MBA from Quantic School of Business and Technology. Anwar's role at Bank of America Merrill Lynch involves performing a cross-functional role from conception to launch of insights related to clients and financial advisors. He collaborates and maintains state-of-the-art technology for the Strategic Data Platform and fulfills analytical reporting needs of business partners by preparing the data, building data models, and applying data visualization techniques. Anwar bridges the gap between Consumer and Wealth Management businesses by establishing relationships between the two vast data sets.