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Data Analyst with less than a year in data analysis, statistical modeling & Power BI.
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Data Analyst and Statistics postgraduate with hands-on experience in data analysis, statistical modeling, dashboard development, and business intelligence. Skilled in Python, SQL, Power BI, and Excel for exploratory data analysis (EDA), data cleaning, visualization, and reporting. Experienced in building regression and clustering models using real-world datasets and generating actionable business insights. Completed internship at the Directorate of Economics and Statistics (DES), improving reporting efficiency and analyzing large socio-economic datasets.
University of Mumbai
Master of science · Statistics
August 1, 2023 – June 30, 2026
Bhavan's College
Bachelors of science · Statistics
August 1, 2020 – June 30, 2023
Directorate Of Economics And Statistics (DES)
Data Analyst
May 1, 2024 – June 1, 2024
India
Street Vendor Socio-Economic Study
June 21, 2026 – Present
Conducted a socio-economic research study on street vendors in Mumbai using a multi-stage stratified sampling design across Central, Western, Harbour, and Trans Harbour railway lines. and collect 400+ data Built a linear regression model in R using stepwise selection, explaining 43% variance in average monthly income and identifying significant socio-economic predictors. Applied K-Modes clustering in Python to identify migration patterns, revealing 3 distinct vendor profiles based on socio- economic and employment characteristics. Identified work duration and food-product type as major factors influencing daily customer count. Generated insights supporting evidence-based urban planning and welfare initiatives under the Smart Cities Mission and PM SVANidhi scheme
DBT Star Advanced Excel Certified
Unknown
June 1, 2026 – Present
HackerRank SQL certified
HackerRank
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects, particularly the 'Street Vendor Socio-Economic Study', show an interest in applying data analysis to real-world social and economic issues, which aligns with roles requiring impact-driven analysis. The internship at a government directorate further indicates an ability to work within structured environments and contribute to public sector initiatives. The breadth of tools and techniques used (Python, R, SQL, Power BI, Excel, statistical modeling, machine learning) suggests adaptability and a willingness to learn diverse technologies relevant to data analysis.
Soft Skills & Operational Fit
The candidate demonstrates an ability to work in a team and communicate with mentors, as evidenced by their internship description. Their project work indicates a structured approach to problem-solving and the ability to derive actionable insights from data. The academic background in Statistics suggests a strong foundation in analytical thinking and quantitative methods.