Vaibhav Garg

AI Researcher

Bengaluru, Karnataka, India8 yrs 6 mos experience

Highly Stable

Key Highlights

Led a global team of data scientists at Goldman Sachs.
Expertise in developing credit and fraud models.
Passionate about applying data science in fintech.

Stackforce AI infers this person is a Fintech expert with a strong focus on data science and fraud detection.

Contact

Skills

Core Skills

Data ScienceCredit Risk ManagementCredit ScoringAnalytical Skills

Other Skills

Big Data AnalyticsCC++CreditCredit Card Fraud PreventionCredit CardsCredit ControlCredit ManagementData AggregationFinTechFraud DetectionHadoopMachine LearningMathematicsMatlab

About

As the Vice President at Goldman Sachs, I led a global team of 10 data scientists for developing and deploying credit and fraud models for the Apple and GM credit card businesses. With 7+ years of experience and expertise in data science and machine learning, I have successfully delivered solutions for various fintech problems, such as credit risk assessment, credit scoring, payment fraud, and credit card transaction fraud. I graduated with a dual degree (B.Tech + M.Tech) from the Indian Institute of Technology, Delhi, in 2017, where I studied electrical engineering and information and communication technology. I am passionate about applying data science and machine learning to solve real-world challenges and create value for customers and stakeholders. I am also an avid learner and a fintech industry enthusiast, with multiple certifications and honors in big data, python, and CFA.

Experience

Kotak mahindra bank

Lead Data Scientist

Jul 2024 – Present · 1 yr 8 mos · Bengaluru, Karnataka, India · On-site

Goldman sachs

4 roles

Vice President

Promoted

Jan 2022 – Jul 2024 · 2 yrs 6 mos · Bengaluru, Karnataka, India

Global Head of Fraud Decision Science & Lead for Loans Credit Decision Science
Currently, leading a global team of 10 data scientists for Credit & Fraud Model Development
Responsible for developing and deploying models for the Credit Card business for Credit Risk Assessment & Fraud Prevention

Credit ScoringMachine LearningProblem SolvingCredit Card Fraud PreventionCredit CardsData Science+7

Associate

Promoted

Jan 2020 – Dec 2021 · 1 yr 11 mos · Bengaluru, Karnataka, India

Decision Sciences, Marcus by Goldman Sachs

Credit ScoringProblem SolvingCredit ControlMathematicsCreditAnalytical Skills+1

Senior Analyst

Promoted

Jan 2018 – Dec 2019 · 1 yr 11 mos · Bengaluru, Karnataka, India

Analyst

Jun 2017 – Dec 2017 · 6 mos · Bengaluru, Karnataka, India

Finomena

Data Science Intern

May 2016 – Jul 2016 · 2 mos · Finomena

1. Worked as Data Scientist Intern at Finomena (8Finatics Mobile Pvt. Ltd.)
2. Designed web crawlers for multiple educational and governmental sources for data agregation using Python HTTP requests, BeautifulSoup packages.
3. Researched and studied more than 30+ journals on Big Data Analytics, and thereby articulating the comprehensive findings to leverage Big Data in Credit Risk Modelling for meaningful analytics.
4. Conceptualised more than 1000+ data points/features based on the credit history of the user according to the CIBIL records and bank statements.
5. Fabricated more than 200+ model parameters based on Call Detail Records as a part of Credit Risk Model Development.
6. Contextualised around 120+ risk scorecard parameters to build the social network of a customer using FB Graph API, and Google API, to assist in scorecard development.

MathematicsAnalytical Skills

American express

Summer Intern - Risk Analytics

May 2015 – Jul 2015 · 2 mos · Gurgaon, India

1. Worked in a team of 12+ people as a Risk Analyst in Credit Card Prospect Acquisition Team at Risk & Information Management – Centre of Excellence (RIM-CoE) Division, American Express
2. Leveraged data and analytics using Legacy Platforms like SQL, SAS, to gain business insights, to develop statistical models predicting the spending patterns of American Express (AmEx) Credit Card prospects.
3. Developed model using the Big-Data implementation of k-Nearest Neighbors (k-NN) algorithm on HADOOP platform, and application of Linear, Logistic Regression, Ranks and Plots transformations and other econometric models.
4. Performed data analytics to understand the customer's beahaviour under various circumstances.

MathematicsAnalytical Skills