About
Entry-level Data Analyst skilled in SQL, Python, Power BI, and Advanced Excel for data analysis, dashboard development, and business reporting. Experienced in data cleaning, exploratory data analysis (EDA), SQL querying, and data visualization tools to generate actionable business insights. Proficient in building interactive dashboards, KPI reporting, and trend analysis to support data-driven decision-making.
Skills & Expertise (39)
Work Experience
Data Analyst Intern
AiSPRY
Present - Present
Analyzed thousands of IVF treatment records using SQL and Python to evaluate KPIs such as Clinical Pregnancy Rate, Live Birth Rate, and Treatment Success Rate. Developed SQL stored procedures to automate KPI calculations across 5+ treatment metrics. Used joins, aggregations, and filtering techniques to process treatment cycle data efficiently. Performed data cleaning and exploratory data analysis using Python (Pandas, NumPy). Conducted correlation and trend analysis to identify factors influencing treatment outcomes. Designed interactive dashboards in Power BI and Tableau visualizing 10+ clinical metrics across patient age groups and treatment types. Improved reporting efficiency by automating data extraction and preprocessing workflows.
Data Analyst Intern
AiSPRY
Present - Present
Analyzed large-scale traffic datasets using SQL and Python to identify high-risk zones, congestion patterns, and violation trends. Built data preprocessing pipelines to handle missing values, datatype conversions, feature engineering, and outlier checks. Performed trend, correlation, and risk analysis on speed behaviour, traffic density, weather impact, and signal efficiency. Created stakeholder-focused interactive dashboards in Power BI for Traffic Authorities, Traffic Police, Emergency Planners, and Infrastructure Teams. Developed KPIs such as Speed Risk %, Violation Index, Accident Severity Metrics, Congestion Risk Score, and Signal Performance Indicators. Implemented geo-spatial visualization (map dashboards) to highlight accident hotspots and infrastructure load distribution.
Quantitative Research Virtual Experience
JPMorgan Chase & Co.
Jan 2026 - Jan 2026
Completed a quantitative research simulation analyzing loan default risk. Analyzed a loan dataset to estimate probability of default (PD) using statistical modeling techniques. Applied dynamic programming to segment FICO scores for improved default risk prediction.
Education
Master of Computer Applications - Acharya Institute of Technology, Bangalore
2019 - 2021 · Afghanistan
B.Sc. Computer Science - BVVS Science College, Bagalkote
2016 - 2019 · Afghanistan
PUC (Science) - S.R.A PU Science College, Banahatti
2014 - 2016 · Afghanistan
SSLC - Shri Basavanda High School, Mahalingpur
2013 - 2014 · Afghanistan
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