
Kiranmai User
@kiranmaiuser1
I turn procurement and retail data into actionable insights with SQL, Python, Excel, and Power BI.
What I'm looking for
I'm building practical data analytics experience through Social Prachar Institute, where I apply Python, SQL, Excel, Power BI, statistics, and data analytics to hands-on assignments and real-world datasets.
In an ongoing procurement and vendor performance analytics internship, I've profiled, cleaned, validated, and assessed 20,000+ records using Excel and SQL. I analyze procurement KPIs, vendor performance, purchasing trends, inventory, and supplier data with joins, aggregations, views, and window functions.
For Eco Shop, I analyzed 525K+ retail transactions using Python and SQL, applying RFM analysis, cohort analysis, customer segmentation, and K-Means clustering. I built Power BI dashboards for revenue, sales growth, AOV, customer segments, and product performance to support data-driven decisions.
Experience
Work history, roles, and key accomplishments
Data Science & AI Trainee
Social Prachar Institute
Mar 2026 - Present (7 months)
Pursuing structured training in Python, SQL, Excel, Power BI, Statistics, and Data Analytics, building a strong foundation in data analysis and business intelligence. Applying data cleaning, data validation, exploratory data analysis (EDA), and data visualization techniques through hands-on assignments and real-world datasets.
Education
Degrees, certifications, and relevant coursework
Vignan's Nirula Institute of Technology & Science for Women's
Bachelor of Technology, Electronics and Communication Engineering
2023 -
Grade: 8.4 CGPA
Pursuing a Bachelor's degree in Electronics and Communication Engineering with a CGPA of 8.4.
DVR & Dr. HS MIC College of Technology
Diploma, Electronics and Communication Engineering
2020 - 2023
Grade: 7.79%
Completed a Diploma in Electronics and Communication Engineering with a score of 7.79%.
Sri Chaitanya Techno School
Secondary School Certificate, General
2019 - 2020
Grade: 98%
Completed SSC with a score of 98%.
Availability
Location
Authorized to work in
Salary expectations
Job categories
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