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Data Analyst with 3+ years in Data Science & Machine Learning
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Data professional with 3.7 years of experience in data analysis, data engineering, and customer service roles. Skilled in Python, SQL, Power BI, and various machine learning techniques. Proven ability to analyze complex datasets, build data pipelines, generate actionable insights, and automate reporting to drive strategic decision-making and improve customer experience. Areas of interest include Data Science, Business Intelligence, and Generative AI applications.
Gokaraju Rangaraju institute of Engineering and Technology
Bachelor of Technology · Information Technology
N/A – June 30, 2021
Litmus World
Data Analyst
November 1, 2024 – Present
Bengaluru, Karnataka, India
Concentrix
Sr. Representative, Operations
July 1, 2024 – November 1, 2024
Hyderābād, Telangana, India
LTIMindtree
Data Engineer
August 1, 2021 – February 1, 2023
Hyderābād, Telangana, India
Analysis of Diabetes Dataset
June 18, 2026 – Present
Developed a machine learning model to accurately predict whether patients have diabetes. Utilized Pandas for data preprocessing, including handling missing values and converting categorical variables to numerical. Employed Matplotlib and Seaborn for data visualization, aiding in EDA. Conducted Exploratory data analysis, Feature Engineering, and Model Training to gain insights into the dataset, identifying trends and patterns. Explored various machine learning algorithms, including linear regression, decision trees, and random forests. Successfully analyzed a diabetes dataset, identifying key factors influencing diabetes prevalence. Such models can have real-world applications in early disease identification and personalized healthcare, ultimately improving patient outcomes and healthcare resource allocation.
Diwali Sales Analysis using Python
June 18, 2026 – Present
Performed data cleaning and manipulation. Performed exploratory data analysis (EDA) using pandas, matplotlib and seaborn libraries. Improved customer experience by identifying potential customers across different states, occupation, gender and age groups. Improved sales by identifying most selling product categories and products, which can help to plan inventory and meet demands.
Data analytics project using python and SQL
June 18, 2026 – Present
This is an end-to-end data analytics project using python and SQL, utilizing a retail orders dataset from Kaggle. Performed data processing and cleaning using pandas and loaded the data into SQL Server. Utilized SQLAlchemy to establish a connection with a SQL Server database. Implemented complex SQL queries to derive business insights, including identifying top 10 highest revenue-generating products, determining the top 5 highest selling products in each region, identifying the month with the highest sales for each category, and analyzing sub-category profit growth by comparing year-over-year performance. Applied common table expressions (CTEs) and window functions to perform advanced data analysis and gain actionable insights. Delivered actionable insights on product performance and sales trends to inform business decisions and strategy development.
Complete Data Science Bootcamp
Unknown
June 1, 2026 – Present
NPTEL certifications in Introduction to Machine Learning Programming
NPTEL
June 1, 2026 – Present
Data Structures and Algorithms using Python
NPTEL
June 1, 2026 – Present
Udemy Certifications in Machine Learning A-Z Introduction to Python
Udemy
June 1, 2026 – Present
Azure Data Engineer Hands-On PySpark for Big Data Analysis
Udemy
June 1, 2026 – Present
Certified by Leetcode in Python
Leetcode
June 1, 2026 – Present
Sql
Leetcode
June 1, 2026 – Present
Pandas
Leetcode
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from retail sales analysis to diabetes prediction and customer feedback analysis, indicates a broad interest in applying data skills across different domains. The certifications in various data science and machine learning topics, along with Python and SQL, show a commitment to continuous learning and skill development. The experience as a Data Engineer and Data Analyst, coupled with academic projects, suggests adaptability and a willingness to take on different roles within the data ecosystem. This breadth of experience and continuous learning aligns well with a dynamic, growth-oriented culture.
Soft Skills & Operational Fit
The candidate's experience descriptions suggest an ability to collaborate with business and IT teams, provide technical guidance, and present insights to stakeholders. The role at Concentrix, though short, indicates customer service skills which can be beneficial in understanding user needs for data analysis. The automation of reports and building of data pipelines suggest a proactive and efficient approach to operational tasks.