Giovanni Cortes
About Giovanni Cortes
Giovanni Cortes is a Capital Management Data Analyst at UBS, where he has worked since 2020. He specializes in data management principles and conducts assessments to ensure data quality across Capital Management processes.
Work at UBS
Giovanni Cortes has been employed at UBS since 2017, holding various positions including Project Manager, Financial Crimes Investigations Analyst, and currently, Capital Management Data Analyst. In his role as Capital Management Data Analyst, which he has held since 2020, he operates in the Greater New York City Area. His responsibilities include acting as a Subject Matter Expert liaison with Finance, Risk, and the Data Management Office to ensure adherence to data management principles across Capital Management processes. He also conducts assessments with Capital Oversight and Pre-Provision Net Revenue teams to identify data quality issues.
Education and Expertise
Giovanni Cortes studied at Bergen Catholic High School and River Dell Regional High School before pursuing higher education. He achieved a Bachelor of Business Administration (B.B.A.) from Pace University - Lubin School of Business. His educational background supports his expertise in finance and data management, which he applies in his current role at UBS. He has developed skills in data quality assessment, stakeholder coordination, and automated data tracking.
Background
Before joining UBS, Giovanni Cortes gained experience in various financial roles. He worked as a Financial Analyst at Provident Bank for one month in 2013 and served as a Risk Analyst at Hudson City Savings Bank from 2013 to 2014. He transitioned to Certified Financial Services as a Financial Representative from 2014 to 2016 and then worked at TD as a Financial Services Representative from 2016 to 2017. His diverse background in finance has contributed to his current analytical capabilities.
Achievements
Giovanni Cortes has made significant contributions in his role as a Capital Management Data Analyst at UBS. He developed an automated model in Excel that streamlined data quality issue tracking, reducing the time required from four days to one hour. Additionally, he conducts front-to-back reviews on data lineage to enhance decision-making processes and coordinates with stakeholders to address data quality issues effectively.