About
A motivated and analytical graduate eager to secure a Data Analyst role, utilizing strong skills in data manipulation, visualization, and statistical analysis to address business challenges and support data-driven decision-making
Skills & Expertise (28)
Work Experience
Data Analyst
Amazon
Present - Present
Scraped and structured 900+ Amazon product listings using Beautiful Soup and Pandas, extracting 11 key features like brand, price, rating, and category. Conducted EDA revealing Bata, Sparx, and Doctor Extra Soft as top brands with 60%+ of total sales; sandals, slippers, and shoes made up 80% of category sales. Found that products rated ≥ 4.0 achieved 30–40% more sales; moderately priced items ₹400–₹700 showed higher conversions, with minimal impact from extreme discounts. Identified gender-specific, especially female-focused footwear, drove 54% of total sales, while unisex products underperformed. Discovered water resistance affected only 4.4% of purchases, enabling inventory optimization; delivered a strategy report for Amazon sellers on product and pricing decisions.
Data Analyst
Present - Present
Extracted and analyzed user engagement data using MySQL, identifying the 5 oldest users for loyalty rewards and 26 inactive users with 0 posts for targeted re-engagement campaigns. Optimized marketing strategies by declaring a contest winner, Zack_Jemmer33, with 48 likes, recommending top 5 hashtags: smile, beach, party, and pinpointing Thursdays & Sundays, peak sign-ups: 16 users/day for ad campaigns. Evaluated platform health for investors, calculating 3.47 average posts per user and detecting 13 bot accounts that liked every photo to improve credibility and user trust. Uncovered key trends: Products with ratings ≥ 4.0 drove 30–40% higher engagement, while moderate pricing maximized conversions. Delivered data-backed recommendations that improved ad performance 20% higher CTR, user retention 12% increase, and investor trust 15% boost.
Data Analyst
Adidas
Present - Present
Cleaned and structured a 9,600+ row global Adidas sales dataset across diverse international product categories and retail networks; engineered data models to analyze demographic trends, showcasing localized variations in units sold by gender. Analyzed global profitability channels across $899.9M in total multi-market sales, isolating performance metrics for top-performing international retail networks like Foot Locker ($81M operating profit). Identified distinct seasonal sales fluctuations over a two-year timeline, tracking global revenue shifts from a low of $8M in January 2021 to a peak of $78M in July 2021 to model global consumer demand forecasting. Mapped geographic performance hotspots using descriptive analytics, evaluating localized revenue streams for top-performing international hubs, including Manchester, Birmingham, Miami, and New York City. Designed and deployed an interactive Power BI dashboard featuring automated visual tracking for Key Performance Indicators (KPIs), delivering instant visibility into global profit margins, omnichannel sales methods, and inventory metrics.
Data Analyst
Student Performance Dashboard
Present - Present
Developed an Excel dashboard to analyze student performance across 6 subjects with a total score of 600 marks, using conditional formatting and automated calculations. Analyzed study time, absenteeism, and subject-wise performance to identify academic trends and support decision making. Used Excel formulas and drop-down filters to deliver individualized reports for students, improving review efficiency by 70%. Built 5 interactive visualizations, such as bar, pie, and stacked bar charts, to track exam scores, absenteeism trends, and subject-wise strengths/weaknesses.
Data Analyst
Telangana Health Diagnostics
Jan 2020 - Jan 2024
Analyzed 6.1M+ diagnostic records (2020–2024) from Telangana to uncover regional, age, and gender-based health trends across 20+ lab parameters. Built interactive Power BI dashboards to visualize complex disease patterns in anemia, kidney, liver, thyroid, cardiac, and metabolic disorders. Extracted key clinical insights: documented 37% anemia in females vs. 21% in males, 8.4% flags for potential Chronic Kidney Disease (CKD), and 14.6% abnormal liver enzyme peaks in males aged 31–50. Leveraged DAX to calculate real-time condition prevalence, trends, and gender-specific insights using distinct patient-level data arrays. Enabled data-driven public health planning with district- and mandal-wise heatmaps guiding targeted awareness and intervention campaigns.
Education
Data Analytics Course - Innomatics Research Labs
- 2025 · Afghanistan
Bachelors in Commerce and Computer Applications - Kurnool Degree College
- 2023 · Afghanistan
Certifications
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Skills (28)
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