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Data Analyst with less than a year in Python, SQL & Power BI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Analyst who improved dataset completeness from 75% to 95% across 3 projects during an 8-month internship at Pyspiders, Bengaluru, building SQL and Python pipelines and Power BI dashboards that informed real-time business decisions across HR, retail, and sports analytics. Proficient in EDA, KPI development, and data storytelling. Seeking entry-level Data Analyst, Business Analyst, or Power BI Developer roles.
Ballari Institute of Technology and Management
B.E. · Artificial Intelligence & Machine Learning
August 1, 2021 – June 30, 2025
Pyspiders
Data Analyst Intern
July 1, 2025 – February 1, 2026
Bengaluru, Karnataka, India
Global Superstore Sales Analysis
July 1, 2025 – February 1, 2026
Analyzed 50,000+ retail transaction records using Python and SQL to uncover sales, profit, customer, and regional performance insights Built an interactive Power BI dashboard using 17 SQL business queries plus a responsive HTML/CSS/JavaScript web dashboard (Chart.js, Leaflet.js), reducing analysis time by 60% through automated KPI tracking and dynamic filtering
HR Attrition Analysis
July 1, 2025 – February 1, 2026
Conducted EDA on 49,000+ employee records to identify attrition drivers: department, salary band, job role, and years at company Engineered features using Pandas/NumPy: encoded categorical variables, computed segment attrition rates (Sales: 20.6% vs R&D: 13.8%), and validated key predictors (overtime, job satisfaction, distance from home) via correlation heatmap and chi-square testing Developed a Power BI executive dashboard with KPIs (Overall Attrition Rate, Avg Tenure, Dept-wise Headcount) to guide HR retention interventions, replacing 3 static Excel reports
IPL Data Analysis
July 1, 2025 – February 1, 2026
Engineered an end-to-end analytics dashboard on 7+ seasons of IPL ball-by-ball data (200,000+ records) using Python (Pandas) for ETL and Power BI for visualization Developed 10+ DAX measures enabling season-over-season performance comparison across 200,000+ IPL records Applied Power Query for data transformation: column merging, conditional columns, and relationship modeling across 3 relational tables with drill-through filters and dynamic slicers for team, player, and match-level exploration Designed a star schema data model with fact and dimension tables to optimize query performance and filter propagation
View ProjectData Analyst Training & Certification
Pyspiders
February 1, 2026 – Present
Achieved a perfect score, indicating comprehensive knowledge and practical expertise in Power BI.
Strengths
Limitations
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive and self-driven approach to learning and applying data analysis techniques across diverse domains (retail, sports, HR). The internship experience at Pyspiders aligns well with a practical, hands-on learning environment. The candidate's stated target role of 'Data Analyst' is a direct match for their skills and experience. The breadth of tools and concepts covered indicates adaptability and a willingness to tackle varied challenges. However, the psychometric test score suggests potential areas for growth in team collaboration and stress handling, which are important for cultural fit in a dynamic work environment.
Soft Skills & Operational Fit
The candidate's project descriptions highlight an ability to communicate complex analytical findings to cross-functional stakeholders, suggesting good presentation and communication skills. The focus on reducing analysis time and enabling self-service BI indicates a results-oriented and efficient approach. The psychometric test score is moderate, suggesting potential areas for development in logical reasoning, work attitude, stress handling, or team collaboration, which would require further probing.
Achieved a perfect score, demonstrating strong foundational and practical skills in data engineering and data platforms.
Strengths
Limitations