Joy Bhatnagar
@joybhatnagar
Passionate electrical engineering student with expertise in data analytics.
What I'm looking for
I am a dedicated and passionate electrical engineering student with a strong background in data analytics. Throughout my academic journey, I have gained valuable experience in utilizing various tools and techniques to analyze and visualize data, enabling data-driven decision-making. During my internship at Tata Power, I built an interactive dashboard using Tableau to visualize and analyze power breakdowns, contributing to the identification of hotspots across multiple districts. Additionally, I developed a prediction model using regression analysis in Python to forecast future losses in consumer hours, based on data collected from different zones. I also conducted knowledge transfer sessions to enhance the usage of visualization tools like Tableau in data-driven decision-making.
As a data analytics intern at the Faculty of Management Studies, I analyzed the financial reporting quality of companies by studying the impact of corporate culture. I developed an algorithm to quantify corporate governance and assisted in designing a normalization algorithm to link company growth with corporate culture. These experiences have equipped me with a strong foundation in data analytics and a deep understanding of the importance of data-driven insights in driving business success.
Experience
Data Analytics Intern
FACULTY OF MANAGEMENT STUDIES(FMS) DELHI
Analyzed the 10K+ filing of 400+ companies to study how corporate culture affects a firm’s financial reporting quality. Developed an algorithm to quantify corporal governance using the Corporate Governance Framework(CVF). Assisted the team in designing a normalization algorithm to link the growth of a company with its corporate culture.
Corporate Operations Services Intern
TATA POWER(TPDDL) DELHI
Built an interactive dashboard to visualize and analyze power breakdowns and identify hotspots across 12 districts using Tableau. Programmed a prediction model using regression analysis on Python to forecast future losses in consumer hours using data spanning over three years, collected from 45 different zones. Conducted knowledge transfer sessions to introduce visualization tools like Tableau to
Availability
Location
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