Nishanth S

Work History

Infosys Ltd.

08.2020 - Current

Cleaned data by handling missing values, outliers, and duplicates using Python libraries such as Pandas and NumPy.
Conducted EDA to identify patterns, trends, and relationships in data using Python visualization tools like Matplotlib and Seaborn.
Performed feature engineering by creating new variables from existing data to enhance model performance, such as calculating patient risk scores from health metrics.
Developed regression models (Linear regression, LASSO, Ridge, Random Forest) to predict health insurance prices based on factors such as age, health condition, and coverage level.
Evaluated model performance using metrics like Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and R2 score.
Developed a machine learning model that accurately predicts health insurance premiums with a 15% improvement in accuracy compared to the previous model, helping the client optimize their pricing strategy.
Conduct regular meetings with clients to gather requirements, present project progress, and discuss analytical findings.

Experis IT

10.2019 - 08.2020

Optimized test coverage with risk-based analysis techniques, focusing on high-impact areas of the application.
Mentored junior testers on best practices, enhancing overall team knowledge and capabilities.
Managed defect tracking systems, ensuring accurate documentation of issues for efficient resolution.
Contributed to the successful launch of multiple software products by rigorously validating features throughout the development lifecycle.
Collaborated with cross-functional teams to identify system requirements and develop effective test strategies.
Participated in post-release reviews to analyze lessons learned from completed projects, driving process improvements for future endeavors.
Identified critical bugs and worked closely with developers to ensure timely resolution, resulting in a more stable product.
Streamlined testing processes by developing reusable test scripts and templates.

Amazon

01.2016 - 06.2017

Evaluated existing policies and procedures, recommending necessary updates to strengthen internal controls against fraud risks.
Identified trends in fraudulent activities by analyzing large datasets, leading to implementation of improved security measures.
Mitigated reputational damage by promptly addressing customer complaints related to fraudulent transactions or account security concerns.
Mentored a cohort of new candidates, providing guidance and support to enhance their skills and ensure smooth transition into the organization.