Karthikeswaren R

AI Researcher

Chennai, Tamil Nadu, India6 yrs 3 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Published paper accepted at IJCNN
Patent submitted for fraud detection improvement
Expertise in synthetic dataset generation using GANs

Stackforce AI infers this person is a Fintech Data Scientist with expertise in AI and machine learning applications.

Contact

Skills

Core Skills

Generative AiData ScienceData Analysis

Other Skills

Large Language Models (LLM)Big DataGenerative Adversarial Networks (GAN)PythonSQLPandasPySparkNatural Language Processing (NLP)Retrieval-Augmented Generation (RAG)Python (Programming Language)R (Programming Language)TensorFlowMicrosoft ExcelC++C

About

I have experience in leveraging artificial intelligence and machine learning in the payments space. My work revolves around research and real world use cases. I have written a paper that got accepted at IJCNN. In addition, my patent on improving fraud detection is submitted at the US patent office. My current work involves the creation of synthetic datasets using GAN models. Back in IIT-Madras, I used to work on EEG biometrics using signal processing and machine learning.

Experience

6 yrs 3 mos

Total Experience

2 yrs 3 mos

Average Tenure

1 yr 9 mos

Current Experience

Playsimple games

2 roles

Lead Data Scientist

Promoted

Mar 2026 – Present · 3 mos · On-site

Senior Data Scientist

Sep 2024 – Apr 2026 · 1 yr 7 mos · On-site

Large Language Models (LLM)Generative AI

Mastercard ai garage

2 roles

Data Scientist 2

Promoted

Aug 2022 – Sep 2024 · 2 yrs 1 mo · Gurugram, Haryana, India

Worked on publishing papers and patents to improve the visibility of our team AI Garage within and outside of Mastercard.
Generated synthetic datasets using Generative Adversarial Neural Network models and oversampled fraudulent transactions which helped us to discover around $20 million per quarter in fraud GDV.
Analysed high-impact and large-scale payment data using SQL and Pandas and identified issuer banks impacted by fraud.
Produced meaningful insights regarding fraud and uncovered 1-2% of approval rates in issuer banks based on scores computed using PySpark.
Involved in using time series models to forecast revenue for various products and their respective stakeholders.

Big DataData Science

Data Scientist

Aug 2020 – Aug 2022 · 2 yrs · Gurugram, Haryana, India

Samsung r&d institute india - bangalore private limited

Intern

May 2018 – Jul 2018 · 2 mos · Bengaluru Area, India

Built a dashboard that collects bugs from Samsung Pay app and cluster them into different categories. The dashboard used Natural Language Processing (NLP) techniques to create vectors from incoming bugs, and cluster them.

Bitwise academy

Intern

May 2017 – Jul 2017 · 2 mos · Coimbatore

I extracted features which are useful for given projects from existing open source datasets. Also, I executed various machine learning algorithms such as ensemble trees for classification and regression.