Shubham Agrawal

CEO

Austin, Texas, United States18 yrs experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in Machine Learning and Deep Learning.
Proven track record in risk management and analytics.
Strong collaboration with cross-functional teams.

Stackforce AI infers this person is a Fintech expert with a strong focus on risk management and data analytics.

Contact

gujarwasia.shubham@gmail.com LinkedIn

Skills

Core Skills

Risk ManagementData Analysis

Other Skills

AnalysisAnalytical SkillsAnalyticsBig Data AnalyticsBusiness AnalyticsBusiness Relationship ManagementCredit ScoringData MiningData ScienceFinancial RiskGAMSHadoopJavaKnowledge SeekerLogistic Regression

About

Seasoned Data Scientist with experience in Deep Learning/Machine Learning, Product incubation, Product Analytics, big data tools, and building intelligent systems across different verticals in payments industry. Work with cross functional teams including policy, operations, compliance, collections, marketing, data technology and product development to develop AI powered product and tools for mitigating risk and improve customer experience. Interested in expanding skill set while working on challenging projects. Specialties: Machine Learning, Deep Learning, Big Data Analysis, Payment Systems, Intelligent systems, Product Incubation, Product Analytics, Tensorflow, Python, Scala, Hive.

Experience

Visa

4 roles

Senior Director

Promoted

Jun 2024 – Present · 1 yr 9 mos

Principal ML Scientist

Jul 2021 – Jul 2024 · 3 yrs

Lead ML Scientist

Promoted

Jul 2018 – Jul 2021 · 3 yrs

Staff ML Scientist

Apr 2015 – Jul 2018 · 3 yrs 3 mos

Paypal

3 roles

Lead Risk Analyst

Apr 2014 – Apr 2015 · 1 yr · Austin, Texas Metropolitan Area

Senior Risk Analyst

Sep 2011 – Mar 2014 · 2 yrs 6 mos · Austin, Texas Metropolitan Area

Risk Management:
Research and evaluate industry trends to identify new alternatives for enhancing credit/fraud risk detection tools, processes and practices.
Partner with product, operations, compliance and engineering teams to develop, implement, and manage strategies to control losses.
Monitor models, rules, analyst performance and incorporate the feedback to continuously fine tune the existing process.
Collections:
Developed a logistic regression model that predicts the likelihood to pay after an account goes into collections. The model score is used to determine the most appropriate collection strategy (appropriate contact channel, internal vs. OCA placement etc.) based on default risk of an account.
Created a contact strategy to optimize the outbound calls and maximize the collection recovery.
Performed adhoc analysis to support collection operations using SAS and SQL. Contributions include evaluating the current operational strategies, enhancing the contact rate and early identification of potential large losses.

Risk ManagementLogistic RegressionSASSQLData Analysis

Risk Intern

Jun 2011 – Aug 2011 · 2 mos · Austin, Texas Metropolitan Area

Data analysis, validation, modeling, statistical testing and segmentation of large data sets to provide robust risk detection solution for seller risk management.
Created dashboards to analyze the performance of different teams in Risk (detection, ops, strategy etc.) and identify target metrics.

Data AnalysisStatistical TestingSegmentationRisk Management

University of texas at austin

2 roles

Research Assistant

Jan 2010 – May 2011 · 1 yr 4 mos

Teaching Assistant

Sep 2007 – Dec 2009 · 2 yrs 3 mos

Teaching Assistant for Engineering Statistics, Geostatistics and Engineering Economics
Conducted weakly recitation sessions
Maintained course web page
Designed homework and assisted in quiz preparation and grading