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Data Analyst with less than a year in Excel and SQL with experience in Python for data analysis.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Entry-level Data Analyst skilled in Excel (pivot tables, dashboards) and SQL, with hands-on experience cleaning and analyzing large retail and operations datasets using Python. Developed interactive dashboards to surface revenue trends and performance gaps, and built reporting systems that improved data accuracy and delivery speed. Strong analytical skills, attention to detail, and a collaborative approach to drive actionable insights for business decisions.
Techno International New Town, MAKAUT
B.Tech · Electrical Engineering
August 1, 2020 – June 30, 2024
Superstore Sales Performance Dashboard
June 1, 2026 – June 1, 2026
Analyzed 9,800+ retail sales records across 4 years to quantify revenue trends, profitability drivers, and regional performance gaps. Identified underperforming regions (South: $386K vs West: $698K), highlighting opportunities for targeted growth strategies. Diagnosed a -3% profit margin in the Furniture category, including a $16.5K loss in the Tables sub-category, informing corrective pricing and product decisions. Demonstrated that 50%+ discounts reduce profit margins to 1.8%, supporting a data-driven discounting and promotion strategy. Built and maintained an interactive Excel dashboard with pivot tables, slicers, KPI cards, heatmaps and charts, delivering weekly performance reports to stakeholders and tracking updates via Git version control. Developed and documented MySQL queries (GROUP BY, CASE WHEN, STR_TO_DATE, NULLIF, aggregate functions) to extract, validate, and reconcile 9,800+ sales records, improving data accuracy by 15%. Collaborated cross-functionally with marketing and finance teams to translate analysis into targeted growth and pricing recommendations.
View ProjectSales & Operations Dashboard
June 1, 2026 – June 1, 2026
Designed an interactive dashboard to track KPIs including total revenue, delivery performance, and category-wise sales across time. Cleaned, transformed, and validated raw datasets using Python (Pandas) and SQL, ensuring consistency and accuracy of reported metrics. Created dynamic visualizations with Pivot Tables, charts, and slicers, partnering with stakeholders to interpret insights and guide decisions.
Python Data Analysis - EDA Project
June 1, 2026 – June 1, 2026
Conducted exploratory data analysis on structured datasets to uncover trends, correlations, and anomalies relevant to business questions. Cleaned and preprocessed datasets by handling missing values, outliers, and inconsistencies to improve model and analysis reliability. Generated statistical summaries and visualizations to support interpretation of results and clear communication of findings.
IBM Generative AI Professional Certificate
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show a focus on practical data analysis applications, which aligns well with a data-driven culture. The diversity of projects (sales performance, operations, general EDA) indicates adaptability. The self-learning initiative (Basic R) and pursuit of certifications (IBM Generative AI) suggest a growth mindset. However, the candidate is entry-level with no professional experience, which might require more mentorship and integration into a professional team environment.
Soft Skills & Operational Fit
The candidate demonstrates a collaborative approach through cross-functional teamwork mentioned in project descriptions. Attention to detail is evident in data validation and reconciliation efforts. The pursuit of competitive exams and certifications suggests a proactive and self-driven learning attitude. However, without specific psychometric or English test scores, a comprehensive assessment of soft skills like logical reasoning, work attitude, stress handling, and team collaboration is not possible.