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Mehul Parashar

Mehul Parashar

Data Analyst

Technology / Internet

Indianapolis, Township of Center, Marion

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Hello! I’m Mehul Parashar, a dedicated data scientist with a rich background in computer information science from Purdue University. My professional journey has been marked by a commitment to transforming complex data into actionable insights, helping businesses make data-driven decisions. At Spotlist Inc., I honed my skills in leveraging advanced analytics and machine learning technologies to enhance business operations and drive strategic initiatives.

Beyond my professional life, I am a passionate soccer fan, often drawing parallels between the strategies on the pitch and those in data analytics. Whether it's exploring new data methodologies or cheering from the sidelines of a soccer game, I bring enthusiasm and a deep commitment to excellence in everything I do. I’m always eager to connect with like-minded professionals and explore innovative solutions in the field of data science.

Approximate rate: $20 per hour

Experience

I have held various positions in data analytics and data science, with significant experience at Spotlist Inc. as a Lead Data Scientist. There, I implemented a streamlined data pipeline, utilized machine learning algorithms, and developed interactive dashboards, significantly enhancing business decision-making processes. My role also involved proposing data-driven strategies to optimize operations. Prior to this, I worked as a Junior Analyst at Dhakad Events and Entertainment in Mumbai, where I conducted data analysis and operational research for a celebrity management company, focusing on data from movies, shows, and celebrities.

Education

I earned my Master's in Computer Information Science from Purdue University, where my coursework covered key areas such as Machine Learning Design, Data Visualization, Cloud Computing, and Database Security. This program equipped me with a robust foundation in both theoretical and applied aspects of data science and analytics, preparing me to tackle complex data challenges in various business contexts.

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