CHETAN SHARMA

• Having 3+ years of experience in Data Analytics & Business Operations for US and UK clients. Proficient in Power BI, SQL Server, Advanced Excel and Python with a talent for advanced reporting, KPI tracking, and business forecasting. Skilled in collaborating with cross-functional teams to deliver measurable improvements in efficiency and performance.

Data Science Intern at Flip-Robo Technologies, Remote, February 2021 — June 2021

Worked on Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly)

• Data analyzing, data visualization
• Web Scrapping
• Using BI tools like Power BI for data analysis involves transforming raw data into insightful visual representations to aid data-driven decision making

Engineer - Machine Learning Developer Intern at Technocolabs Software, Remote, Oct 2021 — Dec 2021

• Develop automated processes for large-scale data analysis, model validation, development, and implementation
• Research, implement, and deploy new machine learning and statistical approaches for profitable business decision-making
• Tools used: Python, ML algorithms with ML libraries, Power BI, and ERP

Engineer - Data Scientist intern at The Sparks Foundation, Remote, February 2022 — July 2022

• Build machines and tune learning models using Python and its libraries (LR and logistic with decision tree models, along with hyperparameter tuning)
• Using BI tools such as Power BI to analyze data, find important patterns, and design visualization dashboards
• Tools used: Python IDE, Visual Studio, SQL Server, Power BI, VBA, and advanced Excel charts

Project: Credit risk and bank personal loan modeling, Source: Kaggle, Remote, December 2021 — January 2022, 

Description: This project is an analysis of customers who accepted personal loan offers

Conclusion: It concluded how various variables affected personal loan acceptance and developed an ML model, 

Skills: Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly), 

Project: Uber Trip Analysis, Remote, November 2021 — December 2021, 

Description: This project is an analysis of rides and rush in New York, 

Conclusion: The study concluded how time affected customer trips and how various users made trips from different bases, 

Skills: Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly)

• IBM certified – Data Science Course
• IBM certified – Data Analytics Associate
• Certified - Business Analytics with Power BI