Results-driven Data Analyst with a strong foundation in SQL, Python, Tableau, and Excel, specializing in statistical analysis, EDA, and data visualization. Proven ability to translate complex datasets into actionable insights that drive profitability, optimize operations, and enhance customer engagement. Eager to leverage advanced analytical techniques to solve complex business challenges, identify growth opportunities, and deliver strategic value in dynamic, data-centric environments.
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Summary
Queried Brazilian e-commerce records (2016-2018) using aggregation, joins, and window functions to analyze customer, order, and payment trends. Identified 136% order value growth, with strong seasonal spikes in November and peak demand in afternoons. Suggested discount campaigns in low-order months and faster deliveries in high-order states to boost engagement.
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Summary
Analyzed customer records (age, income, fitness, usage patterns) to segment buyers into distinct profiles. Identified three customer personas: entry-level buyers (avg. income $46K, 83 miles/week), mid-tier buyers (avg. income $49K, 88 miles/week), and premium customers (avg. income $75K, 167 miles/week). Proposed segmented marketing strategies are projected to increase premium model sales by 20% and reduce acquisition costs for entry-level products by 15-20%.
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Summary
Processed 550k+ transactions to evaluate demographic patterns in consumer spending. Performed EDA and statistical sampling, uncovering that males spent 8% more, the 26-35 age group generated the highest sales, and unmarried users were more active buyers. Recommended targeted promotions to maximize seasonal sales to improve conversion in key demographics by 12-15%.
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Summary
Analyzed 10k+ rental records to identify demand patterns based on season, weather, working days, and holidays. Applied T-tests, ANOVA, and Chi-Square to validate demand differences; found significant demand variation across season and weather, but not between weekdays and weekends. Identified peak demand in clear weather and during summer/autumn seasons, validating the business impact of environmental factors.
SQL, Python, Microsoft Excel, Tableau, MySQL, BigQuery, NumPy, Pandas.
EDA, Hypothesis Testing, Probability & Statistics, Statistical Analysis, Data Visualization.
Strategic Thinking, Analytical Reasoning, Attention to Detail, Stakeholder Communication.
Pricing Analyst - Trainee
Jaipur, Rajasthan, India
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Summary
Analyzed complex pricing data for 15+ clients, developing robust dashboards and insights to inform strategic decisions and optimize profitability.
Highlights
Developed and maintained a centralized Excel database by extracting and aggregating weekly pricing data for over 15 clients, improving data accessibility and integrity.
Calculated critical KPIs, including profit margins and loss metrics for diverse client portfolios, providing clear financial performance indicators.
Designed and implemented Tableau dashboards, linking directly to Excel models to visualize client-specific profitability and pricing trends for key stakeholders.
Conducted comparative analysis of current and historical pricing data across clients, pinpointing significant pricing shifts and their impact on profit margins.
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Program
Data Science and Machine Learning
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Bachelor
Commerce