Sri Sountharya K R

Data Engineer

[email protected] +91 9597258435

Resume

Hello, I am

Sri Sountharya K R.

1

Excel
Project

1

PowerBI
Project

3

Python
Projects

About Me

Welcome to my portfolio website!
I’m Sri Sountharya K R, a passionate Data Analyst / Data Engineer skilled in SQL, Python, Power BI, and Tableau, with 4+ years of hands-on experience transforming data into real business value.

From leading ETL pipelines and mentoring 50+ learners to driving insights across political campaigns, e-commerce, and logistics, I specialize in EDA, feature engineering, and building compelling dashboards.

My work has boosted campaign engagement by 40%, improved forecasting models by 15%, and enabled smarter decision-making across teams. I love turning complex data into clear, actionable stories through Power BI and Tableau.

Currently pursuing a Master’s in AI & ML, I’m driven by curiosity and problem-solving. If you're looking for someone who blends technical expertise with strategic thinking, let’s connect!

Key Skills

SQL

PYTHON

TABLEAU

POWER BI

EDA

MS EXCEL

NUMPY

PANDAS

My Projects

Sales Analytics (FMCG)

Domain/Function: Market, & Customer Performance Analytics

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply chain

Domain/Function: Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply chain

Netflix Data Cleaning and Analysis Project

Domain/Function: Netflix Data Cleaning and Analysis Project

Delhivery – Feature Engineering for Logistics Forecasting

Domain/Function: Delhivery – Feature Engineering for Logistics Forecasting

Health Insurance Cost Prediction using Machine Learning

Domain/Function: Machine Learning

My Experience

Experienced

Data Analyst- FreeLancer
Dec 2020 - Oct 2024

Delivered personalized coaching in SQL, Python, and Tableau to over 50 learners.

· Developed real-world case studies focused on ETL, EDA, and dashboarding.

· Mentored learners in completing capstone projects and transitioning into analytics roles.

Senior Associate India Political Action Committee (I-PAC)
Sep 2019 – Dec 2020

· Led a team of 20+ in the Women Empowerment Wing, launching programs that boosted local community participation by 30%.

· Led analytics on 500+ citizen datasets to inform campaign strategy. Built survey dashboards and SQL queries to track impact metrics.

· Enabled data-driven improvements in public scheme implementation. Crafted persuasive speeches for a senior political leader, driving a 25% increase in media visibility and audience engagement.

· Engaged with over 500 citizens through outreach and surveys, providing insights that influenced key campaign and policy decisions.

· Streamlined government scheme processes, resulting in a 15% improvement in administrative efficiency and service delivery.

· Delivered media training for political spokespeople, enhancing communication skills and elevating public image by 20%. \

Developed strategic social media content, achieving a 40% increase in engagement and reach across multiple platforms.

Career Transitioner

Research Engineer

Vetri IAS

Jun 2017 – Sep 2019

Developed data-driven content strategies across digital platforms, increasing audience engagement by 30%.
Led a content team to curate timely current affairs resources, improving resource accessibility for over 500 candidates.
Conducted engaging current affairs and history classes for Civil Services candidates, enhancing their exam readiness.
Mentored competitive examination candidates, providing tailored guidance that improved their success rates by 25%.
Administered multi-level test series and mentorship programs, significantly boosting candidate performance and confidence.
Managed the institute's social media presence, increasing follower engagement by 40% and enhancing brand visibility.
Supervised a team of 20 in producing daily current affairs content, directly supporting UPSC Civil Services aspirants.

Awards & Certificate

Python Libraries

SQL

EDA Fundamentals

Excel

Let's Connect

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

Mail Me

[email protected]

https://www.linkedin.com/in/k-r-sri-sountharya-743a8786

Call Me

+91 9597258435

GitHub

https://github.com/SountharyaKR

Excel Project

Sales Analytics (FMCG)

Domain/Function: Market, & Customer Performance Analytics

Created a comprehensive Excel dashboard to help the sales team evaluate customer-wise performance, track YoY growth, and analyze market trends against targets across multiple regions, enabling data-driven decision-making and strategic planning.

Visualized YoY growth of top Indian customers. Identified key contributors like Amazon, Atliq, and Croma using Excel dashboard.

Analyzed country-wise sales vs targets. Highlighted underperforming markets and revenue gaps using conditional formatting.

Project Details

In this project, I created a market and customer performance dashboard using Excel. It integrates sales data from 2019 to 2021 and provides an interactive view of:

Country-wise performance

Market vs target analysis

Customer-wise growth in India

Using pivot tables, slicers, conditional formatting, and report beautification techniques, I developed a tool that helps the business track revenue, identify growth opportunities, and improve decision-making. The dashboard highlights top customers like Amazon and Croma, as well as underperforming regions, helping optimize marketing and sales strategies.

Skills Learned:
Pivot Table

Power Query

DAX (Basics)

Conditional Formatting

Report Beautification

Sales Domain Metrics

This project empowered me to present actionable insights from raw data using Excel and to support data-driven decision-making in real business scenarios.

PowerBI Project

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply chain

Domain/Function: Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply chain

AtliQ Hardwares is growing fast but struggling to compete due to reliance on Excel for reporting. This project introduces a Power BI solution designed to modernize analytics, offering stakeholders clear insights and enabling smarter, faster decision-making across the business.

Analyzed forecast accuracy, net error, and risk by customer and product segments. Identified key drivers of excess inventory and declining net profit.

Evaluated product and regional profitability using gross margin, unit economics, and performance matrix. Identified loss-making segments across market

Project Details

The goal of this project was to build a unified Power BI dashboard that could serve multiple departments—sales, marketing, finance, and leadership—with actionable, drill-down insights. The report was built with a focus on:

Robust Data Modeling

User-friendly and intuitive report design

Drillable, role-specific views

What I Learned:
Power Query (basic to advanced transformations)

DAX (simple to complex calculations)

Data modeling with 10+ interrelated tables

Visual selection and dashboard design best practices

Bookmarking for guided navigation

Deploying reports to Power BI Service

Incorporating stakeholder feedback

Business KPIs for Sales, Marketing, Finance & Supply Chain

This project demonstrates my ability to convert raw data into insights using Power BI, create clean reports for diverse teams, and align business metrics with strategic decisions

Python Project

Netflix Data Cleaning and Analysis Project

Domain/Function: Netflix Data Cleaning and Analysis Project

Explored and visualized Netflix content using Python, revealing trends in genre, ratings, country-wise content, top creators, and audience sentiment using EDA, Plotly, and TextBlob analysis.

View Project
on GitHUB

Performed sentiment analysis on Netflix content; majority of shows had a positive tone, especially post-2015.

Netflix content production peaked in 2018, with movies consistently outpacing TV shows until a sharp drop post-2020.

Project Details

In this project, I performed an end-to-end analysis of the Netflix dataset using Pandas, Seaborn, Plotly, and TextBlob for sentiment analysis. With over 8800 titles, I explored:

📊 Distribution of movies vs TV shows

🌍 Top contributing countries (e.g., USA accounts for ~32%)

🎭 Viewer rating categories and content volume

🎬 Top 5 directors and actors by appearance

📈 Trends in content production by year (peak in 2018)

😄 Sentiment analysis of content descriptions

The project also involved data cleaning, visual storytelling, and deriving business insights, like the rise in teen and mature content. Sentiment trends over time revealed a dominance of neutral and negative tones in recent content.

This project demonstrates my ability to handle real-world datasets, generate insights, and build compelling visual narratives with Python.

Python Project

Delhivery – Feature Engineering for Logistics Forecasting

Domain/Function: Delhivery – Feature Engineering for Logistics Forecasting

Prepared and transformed logistics trip data to support forecasting models by extracting meaningful features, optimizing data types, and enhancing analysis readiness.

View Project
on GitHUB

Maharashtra, Karnataka, and Haryana emerged as top trip origin states, indicating high delivery activity and logistical demand in these regions.

Identified strong positive correlations between total trip time, scan durations, and distances—helpful for optimizing delivery time features.

Project Details

Worked on a real-world logistics dataset from Delhivery, India’s leading supply chain platform, to clean and structure over 144K records of trip-level data. Applied advanced feature engineering techniques to derive key variables such as trip duration, segment times, route types, source-destination mapping, and hourly, daily, weekly time splits.

Performed data type optimization and reduced memory usage by over 40%. Created state-wise and city-wise aggregations to reveal top-performing locations. Used hypothesis testing to compare actual trip time vs estimated trip time and evaluated correlations between operational metrics using heatmaps and pairplots.

This project showcases the ability to handle large-scale logistics data, apply EDA, build features for ML readiness, and generate actionable insights for optimizing delivery operations.

Python Project

Health Insurance Cost Prediction using Machine Learning

Domain/Function: Machine Learning

Built a Streamlit web app to predict individual health insurance costs using regression models. Inputs include age, income, lifestyle, and medical history. Delivers real-time premium predictions through a clean, interactive interface.

View Project
on GitHUB

View Project
on Streamlit

A Streamlit app that predicts health insurance costs based on user inputs like age, income, medical history etc.. Clean UI for real-time predictions.

A heatmap showing feature correlations with insurance premiums. Highlights strong predictors like age, income, insurance plan using visual insights.

Project Details

This project leverages machine learning to predict health insurance premiums based on user demographics, health habits, and medical history. The app was built using Streamlit for the front-end and scikit-learn for model training.

The prediction system:

Uses separate models for younger individuals (≤25) and the rest for improved accuracy.

Includes a custom medical risk scoring mechanism.

Normalizes user input using pre-trained scalers.

Outputs real-time premium predictions on a user-friendly interface.

Key Tools: Python, Pandas, Scikit-learn, XGBoost, Streamlit, Joblib
Use Case: Helpful for insurers to estimate premiums and for individuals to understand their risk factors.