Shelvi Garg
About Shelvi Garg
Shelvi Garg is a Data Scientist with experience in developing advanced predictive models and real-time systems. She has worked at EasyGov and currently contributes to Spinny, where she focuses on improving lead scoring and loan disbursement processes.
Work at Spinny
Shelvi Garg has been employed as a Data Scientist at Spinny since 2022, contributing to various data-driven projects in Gurugram, Haryana, India. In this role, she engineered a real-time lead scoring system that processes leads every 1.5 seconds during peak times. This system enhances the efficiency of lead management, allowing for quicker responses to potential customers. Additionally, she developed a license plate masking system utilizing YOLOv8 and the Segment Anything model, achieving 98% accuracy and significantly reducing costs associated with Photoshop expenses.
Previous Experience at EasyGov
Prior to her role at Spinny, Shelvi Garg worked at EasyGov (Surajya Services Limited) as a Research and Development Analyst from 2019 to 2020 for a duration of nine months in Noida, Uttar Pradesh, India. During her time there, she focused on research and development initiatives that supported the company's objectives. This experience laid the groundwork for her subsequent career in data science.
Education and Expertise
Shelvi Garg holds a Bachelor of Technology (BTech) degree in Information Technology from JSS Academy of Technical Education, Noida. Her educational background provides her with a solid foundation in technology and data analysis, which she applies in her professional work. She has developed expertise in machine learning and data science, demonstrated through her projects and contributions in the field.
Achievements in Data Science
In her data science career, Shelvi Garg has made significant contributions to various projects. She developed a dynamic lead scoring model using XGBoost that reduced agent call volume by 20% while maintaining conversion rates. Furthermore, she contributed to a 10% increase in successful loan disbursements through the creation of an advanced XGBoost model for predicting car loan interest rates, achieving 94.2% accuracy and improving the previous system's performance by 15%.
Writing and Sharing Insights
Shelvi Garg actively shares her knowledge and experiences in data science and machine learning through her writings on Medium. Her articles cover a range of topics related to the field, providing insights that benefit both practitioners and enthusiasts. This engagement reflects her commitment to the data science community and her desire to contribute to ongoing discussions in the industry.