Aniket Das

About Me

Experience

Education

Achievements & Certifications

Aniket Das is currently pursuing a Master of Technology in Computer Science at the Indian Statistical Institute in Kolkata. He achieved an All India Rank of 9 in the ISI Admission Test for M.Tech in Computer Science and attained a 98.55 percentile in the GATE CS 2024, conducted by IISc Bangalore. Before joining the ISI, Aniket worked as a Software Engineer at Cognizant, focusing on Java development and testing. Over nearly three years, he gained extensive experience in software development, security, and vulnerability management.
His academic interests include Data Science and Machine Learning, particularly in the fields of Large Language Models and Natural Language Processing. He actively engages in implementing and experimenting with models in these areas, combining a strong theoretical understanding with practical application.
Aniket is always open to making meaningful connections and collaborating on projects that bridge cutting-edge research with real-world impact. If you have any inquiries or would like to connect, please feel free to contact, or book a call. View Resume

Jr. Software Engineer 2022-2023
Cognizant Hyderabad, India
- Developed a Custom Identity Provider – eSign Login Application for a renowned US based biopharmaceutical company.
- The Custom IdP acts as a one stop solution to the client applications for authentication and authorization of its employees and partners, irrespective of the IAM services or protocols used.
- It supports industry standard protocols like OIDC, SAML, WS-Fed, and IAM services like Okta, PingFederate, TruU to provide a seamless Single Sign-On experience to user, and can be customized as per client requirements.
- Tools & Technologies: Spring Framework, ReSTful Web Services, OIDC, SAML, WS-Fed, Okta, TruU, AD, Core Java.
Software Engineer Trainee (GenC Next) 2021-2022
Cognizant Hyderabad, India
- Worked as a Google Play Protect - Application Security Engr., rev. engg. and reporting over 2000+ live apps.
- Developed NSR (Nano-scorer Review) and reviewed documentations of fellow analysts as Team QC.
- Debugged critical production bugs and resolved appeals on DisruptiveAds, VPN AdFrauds, Spywares, etc.
- Tools & Technologies: Google Tools, Vulnerability Mgmt., Penetration Testing, Reverse Engg., GCP, Core Java.
Software Engineer Trainee (Intern) 2021
Cognizant Hyderabad, India
- Developed an interactive Claims Management System performing CRUD operations using Spring and ReSTful APIs.
- Tools & Technologies: Spring Framework, ReSTful Web Services, MySQL, Microservices, GCP, AWS, Core Java.

Master of Technology in Computer Science 2024-Present
Indian Statistical Institute Kolkata, India
Percentage: 74% (Sem I & II)
Bachelor of Technology in Computer Science & Engineering 2017-2021
Techno Main – Salt Lake Kolkata, India
GPA: 8.74
CBSE Senior School Certificate Examination (Class XII) 2015-2016
Kendriya Vidyalaya Chittaranjan, India
Percentage: 78%
CBSE Secondary School Examination (Class X) 2013-2014
Kendriya Vidyalaya Chittaranjan, India
CGPA: 10.00

ISI Admission Test Merit List (AIR 9) ISI Kolkata
GATE Score Card (98.55%ile) IISc Bangalore
Professional Cloud Architect Google
Associate Cloud Engineer Google
Master SAML 2.0 with Okta Udemy
The Complete Web Development Bootcamp Udemy
Java and Spring Framework with Spring Boot Udemy
Machine Learning with Python IBM
Sentiment Analysis with Sklearn Coursera
Cognizant Cheers Award Cognizant

Projects

Hush - OAuth2.0

A webapp to post secrets and confessions anonymously, authenticated using OAuth 2.0.

Claims Management System

A mediclaim management webapp catering to user requirements by providing them with services to submit claims, view claim status, and show available policies.

Music Genre Classification System

A classification system designed to predict the genre of any musical track, achieved by training the machine using CNN.

Campus Placement Prediction

An ML model designed to predict the employability of students, achieved by training the machine using logistic regression.