Work Experiences

Software Developer
Media Forensic Hub, Clemson University (Aug 2023 - Dec 2024)

• Engineered advanced software solutions to detect and mitigate troll activities across online media platforms.
• Collaborated with interdisciplinary teams to design, code, and test scalable applications for real-time troll detection.
• Utilized cutting-edge technologies, including Python, Java, and machine learning frameworks, to enhance detection accuracy.
• Applied natural language processing techniques to identify patterns of troll behavior and improve content moderation.
• Performed rigorous code reviews and debugging to ensure the reliability and robustness of detection algorithms.
• Contributed to project planning and requirement analysis, aligning detection strategies with organizational objectives.
• Documented technical designs and created user guides to support system maintenance and future enhancements.
• Applied machine learning and software development skills to digital forensics challenges.

Project Engineer- Software Developer
WIPRO (June 2021 - Dec 2022)

• Designed the Front-End applications, user interactive (UI) web pages using web technologies like HTML, CSS, JavaScript, and jQuery.
• Implemented AJAX functionality using JQUERY, JSON and XML.
• Designed new classes and functionalities using various JQUERY components for CRM application for customer service.
• Developed non-functional HTML, CSS pages from the mock ups and involved in Ul review with Ul architect and Business Units.

Teaching Assistant Statistical Methods
Clemson University (May 2024- Dec 2024)

• Assisted in teaching fundamental and advanced statistical concepts, including descriptive statistics, probability distributions, hypothesis testing, ANOVA, and regression analysis.
• Guided students through complex data analysis problems, helping them develop a strong understanding of statistical methods and their applications in research and industry.
• Supported the professor in creating instructional materials, grading assignments, and providing feedback to students, ensuring a comprehensive learning experience.
• Conducted office hours to offer personalized assistance with statistical software (JMP) and interpretation of statistical results, enhancing students' analytical skills.
• Collaborated in the design and delivery of assessments to evaluate students' proficiency in statistical techniques, contributing to the course's overall educational goals.

Teaching Assistant for Data structures and Algorithms
Coding Ninjas (May 2022- August 2022)

• Assisted 500+ students in Debugging codes
• Helping students in their assignments & various projects.

Machine Learning Intern
Internshala (June 2020 - August 2020)

• Trained a predictive churn model with a 92% accuracy rate, analyzing over 1 million customer data points for a leading banking firm, attaining a 10% reduction in customer churn.
• Guided a cross-functional team in deploying the model within a real-world banking environment, ensuring seamless integration.
• Mastered Python, scikit-learn, and pandas for comprehensive data analysis and modeling, leveraging Snowflake for advanced data warehousing and analytics scalability resulting in a 20% increase in data warehousing.

Content Writer
Hahnode FreeTime

Published Articles in Hahnode

Article series on Linear Algebra for Machine Learning 

- This article series delves into the intricate relationship between linear algebra and machine learning, providing readers with a vivid geometric understanding of abstract algebraic concepts. It serves as a bridge between theoretical mathematics and practical machine learning applications, offering a fresh perspective that caters to both beginners and seasoned professionals in the field.


Article Series on Probability for Machine Learning 

- A thoughtfully crafted series of articles designed to unravel the complexities of probability theory in the context of machine learning. The series provides a foundational understanding of probabilistic models and the role they play in developing predictive algorithms. Through this work, I aimed to bridge the gap between theoretical statistics and practical machine learning applications, making the concepts accessible to a broad audience of enthusiasts and practitioners.

Updates: #1 | #2 | #3 | #4 | #5 | #6 | #7 | Final