For my current role at Citibank - Global Fraud Prevention team, I am responsible for managing fraud prevention strategies on digital channels for Credit Cards, Retail Services, and Citi Private Bank to reduce fraud exposure, and improve identification of fraud patterns; minimizing fraud loss using R, SAS, SQL, and Machine Learning techniques. My analytical role has resulted in the prevention of gross fraud amount of $2.4MM quarterly and rapid identification of Account Take Over (ATO) events with non-monetary transactions and analyze customer behavior for improving authentication strategies to detect fraud on compromised accounts. This job involves extensive use of data visualization tools such as Tableau and Power BI to develop and share insights related to the fraud trends on our consumer products (Retail and Credit Cards) to multifarious teams such as Risk, Product, and Legal as well as to the US Consumer banking leadership. I am also responsible for streamlining our risk controls at Citi post - Office of the Comptroller of the Currency (OCC) fine for effective risk management, data governance programs, and internal controls. I am currently working with Fraud leadership directly for the same.

Personal information
Full name: Siddharth Uppal
User name: sid25393
Organization memberships
Not a member of any organization.
Awards
No awards received yet.
Volunteer background
Education: Master's on MS - Industrial Engineering with Data Science and (New York University)
LinkedIn profile
Volunteer availability
Start date: Dec. 9, 2020
End date: None
Hours available per week: 10
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
Data > 1TB
SQL
Data in Text Files
Data in Relational Databases
Experience working on real-world problems using data
Data Visualization
Experimental Methods (RCTs, A/B testing, etc.)
Data Analysis
Time Series Models
Random Forests
Decision Trees
SAS
R
SPSS

Volunteer projects

Project name Organization name Social impact area Project summary Task name Task status
Covid Response Simulator // Scenario Planning for Non-Pharmaceutical Interventions (NPIs) Covid Act Now Education The COVID Response Simulator is a localized, customizable version of the public Covid Act Now (CAN) model. With it, you can take a powerful SEIR epidemiology model and customize it for your county to help plan your response to COVID. The inputs and assumptions in the simulator are modifiable and can be changed to reflect your local realities. In addition, you can project the impact of specific Non-Pharmaceutical Interventions (NPIs) for your county, such as closing schools, restricting business activities, and canceling large events. Based on your inputs, the simulator generates data and graphs illustrating COVID forecasts with and without these NPIs, including estimated case numbers and hospitalizations. Project scoping Started