Daniel A
- Research Program Mentor
MS at University of California Berkeley (UC Berkeley)
Expertise
Financial services, humanitarian aid, public policy
Bio
I am a data scientist currently working as a Presidential Innovation Fellow supporting innovation and modernization efforts within the US federal government. Prior to this experience, I served as a senior data scientist at Workday, an enterprise software company. Prior to Workday, I served as a data scientist at the United Nations World Food Programme (WFP) in the cash transfers unit. My experience entailed developing analytical solutions to support country offices around the world in their operations. Prior to joining WFP, I was a Senior Quantitative Risk Analyst at USAA for four years in a financial risk management capacity supporting the organization achieve its regulatory mandates. Prior to that, I worked at the Federal Reserve Bank of New York for six years in a Risk Associate role. I have expertise in Python and R programming, statistical analysis and data science project deployment. My personal interests include public policy, global affairs and finance. My hobbies include looking after my two daughters (6 and 2 and half years old, respectively). I am interested in honing the interest in data science of young people.Project ideas
Voter propensity project
Communication un⩘Breakdown is focused on using technology and data science to help community organizers reach specific populations for an empathy-based citizen engagement program known as “Deep Canvassing.” Leveraging a close relationship with People’s Action, voter demographic data, and responses from former and active Deep Canvass campaigns, we apply supervised machine learning and reinforcement learning techniques for our MVP, “Dynamic and Responsive Targeting System,” or DARTS, to find undecided voters for the 2020 U.S. Presidential Election, and subsequently, the Georgia Senate runoff. https://www.ischool.berkeley.edu/projects/2020/communication-unbreakdown