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Data Analyst with less than a year in SQL, Python & Power BI
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Assessing your cultural and operational fit
Results-driven Data Analyst with proven expertise in transforming complex datasets into actionable business insights. Skilled in SQL, Python, Power BI, Tableau, and Excel with hands-on experience analyzing 100+ records to improve business decisions by 25%. Demonstrated ability to build automated data pipelines reducing manual processing time by 40%. Strong foundation in data engineering, statistical analysis, and machine learning with a passion for solving real-world problems using data.
Maturi Venkata Subba Rao (MVSR) Engineering College
Bachelor of Technology · Computer Science & Engineering
December 1, 2021 – May 1, 2025
Full Stack Academy
Data Analyst Intern
November 1, 2025 – Present
Hyderābād, Telangana, India
ALMANET - Alumni-Student Networking Platform (AI/ML & Database)
January 1, 2020 – December 31, 2021
Designed and developed a centralized alumni-student networking platform to strengthen academic-industry connections. Built a scalable alumni database to manage profiles, skills, interests, and professional backgrounds efficiently. Implemented AI-driven recommendation algorithms to match students with alumni based on interests, skills, and career goals. Applied machine learning techniques such as similarity scoring and content-based filtering to enhance mentor-mentee matching accuracy. Optimized data processing and database queries to ensure fast, reliable, and scalable system performance. Enhanced mentorship and community engagement through personalized networking recommendations and structured user profiling.
Road Accident Analysis Dashboard
January 1, 2020 – December 31, 2021
Analyzed and understood a 2020-2021 road accident dataset, identifying key attributes such as accident severity, vehicle type, road type, location, light conditions, and casualty counts to define meaningful KPIs. Performed data cleaning and transformation using Power BI Power Query by handling missing values, removing duplicates, standardizing categorical fields, and preparing the data for analysis. Designed and implemented an optimized data model using fact and dimension tables with proper relationships (star schema) to ensure accurate aggregations and efficient performance. Created DAX measures and calculated fields to compute key metrics including total casualties, fatal/serious/slight casualties, year-over-year comparisons, percentage changes, and monthly accident trends. Developed an interactive Power BI dashboard with slicers, maps, charts, and trend visuals to analyze accidents by year, vehicle type, road type, urban vs rural areas, and lighting conditions, enabling data-driven insights.
Earthquake Monitoring Dashboard
January 1, 2013 – December 31, 2013
Analyzed 2,872+ global magnitude 6+ earthquake events recorded between 1900 and 2013. Designed interactive dashboards to monitor seismic KPIs including average depth, station coverage, RMS error, and detection gaps. Evaluated monitoring efficiency using Distance to Station (DMIN) and Coverage Gap (GAP) metrics. Identified high-risk regions with sparse seismic coverage to support disaster preparedness planning. Implemented data cleaning and preprocessing pipelines to handle missing or inconsistent seismic records. Conducted temporal trend analysis to study changes in seismic activity patterns over decades. Created automated visual alerts for abnormal seismic activity to aid rapid response initiatives. Generated comprehensive reports combining GIS maps, charts, and tables for policy-making stakeholders.
Microsoft Certified: Data Analyst Associate
Microsoft
June 1, 2026 – Present
Introduction to Networks (CCNAv7)
Cisco Networking Academy
May 1, 2024 – Present
Database Programming with SQL
Oracle Academy
June 1, 2023 – Present
Software Engineering (CS302)
Saylor Academy
January 1, 2023 – Present
Python Programming Certification
Spoken Tutorial
July 1, 2022 – Present
Cultural Fit Analysis
The candidate's projects show a diverse application of data analysis skills, from earthquake monitoring to road accident analysis and an alumni networking platform. This breadth suggests adaptability and an interest in applying data science to various domains. The 'ALMANET' project, involving AI/ML for matching, indicates an interest beyond pure data analysis, which could be a strong asset. The current internship as a Data Analyst Intern aligns well with the target role. However, the candidate is still pursuing a Bachelor's degree, which might indicate a need for more structured mentorship in a professional setting.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving skills through project work and an ability to collaborate cross-functionally, as noted in their internship description. Their project descriptions indicate a structured approach to data analysis, from cleaning to visualization and reporting. The automation of reports suggests an efficiency-oriented mindset. However, without specific psychometric test results, a deeper assessment of work attitude, stress handling, and team collaboration is limited.