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Data Analyst with less than a year in Data Analysis & Python
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Assessing your cultural and operational fit
Detail-oriented B.Tech Computer Science graduate (expected June 2026) with hands-on experience in data analysis, KPI reporting, dashboard creation, and scheduled report generation across 100,000+ record datasets. Proficient in Python (Pandas, NumPy, OOP), SQL, Power BI, and Microsoft Excel. Skilled in data cleaning, exploratory data analysis (EDA), statistical analysis, predictive analytics, data reconciliation, and translating complex datasets into actionable business insights. Strong team player with proven ability to work independently, communicate findings clearly, and deliver accurate, timely analytical outputs.
Parul University
B.Tech · Computer Science Engineering
August 1, 2022 – June 30, 2026
E-Commerce Customer Geography Analysis
June 19, 2026 – Present
Designed and implemented reusable Python (OOP) data pipelines to process and analyse 100,000+ e-commerce records, automating data cleaning and reconciliation workflows and resolving 18% data inconsistencies. Built 10+ Power BI dashboards identifying top-3 regions contributing 62% of total revenue; translated complex regional purchasing patterns into written business insight summaries for stakeholder review. Generated a full suite of scheduled regional KPI reports supporting marketing and logistics decision-making across large-scale datasets. Documented all data preparation and reporting processes in SOP-driven format to ensure reproducibility, quality assurance, and team knowledge transfer.
E-Commerce Delivery Delay Analysis
June 19, 2026 – Present
Conducted end-to-end KPI and predictive analysis on 100,000+ delivery records; classified 11% of orders as delayed and identified a 25% seasonal surge through trend, distribution, and statistical analysis. Performed root cause analysis isolating 2 logistics bottlenecks responsible for 40% of all late deliveries; developed metric report dashboards supporting a 15% delay reduction framework. Independently managed full reporting workflow from data ingestion to insight delivery under defined deadlines; reconciled order records across datasets to verify data consistency and completeness.
Student Academic Performance Analysis
June 19, 2026 – Present
Analysed 500+ student records using descriptive statistics to uncover a 20% performance gap across academic quartiles; produced stakeholder-ready visualisation reports and written summaries. Optimised Python (Pandas) data preprocessing pipeline using modular, reusable code design, reducing manual effort by ~30% and improving overall reporting efficiency and workflow reproducibility. Documented analytical methods to support peer knowledge transfer and team onboarding.
Deloitte Data Analytics Job Simulation
Forage
June 1, 2026 – Present
Tata GenAI Powered Data Analytics Job Simulation
Forage
June 1, 2026 – Present
Certified Data Analyst Foundations
Udemy
June 1, 2026 – Present
Advanced Excel: Formulas, Functions & VBA Macros
Udemy
June 1, 2026 – Present
SQL (Basic)
HackerRank
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a diverse application of data analysis skills across different domains (student performance, e-commerce logistics, customer geography). Their proactive pursuit of certifications and virtual job simulations (Deloitte, Tata GenAI) indicates a strong drive for continuous learning and alignment with industry best practices, suggesting a good cultural fit for a growth-oriented environment. The focus on documentation and knowledge transfer also points to a collaborative mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills such as attention to detail, ability to work unsupervised, and effective written and oral communication, which are crucial for an independent data analyst role. Their project descriptions highlight a structured approach to problem-solving and a focus on reproducibility and documentation, indicating good operational fit.