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Data Analyst with less than a year in Data Analysis & Business Analysis
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Analytical and detail-oriented professional with 1+ year of experience across Data Analysis, Business Analysis, MIS Reporting, and Operations Analytics. Proficient in extracting, cleaning, and analyzing complex datasets to identify trends, risks, and business insights. Skilled in building MIS dashboards, KPI reports, financial performance trackers, and automated data pipelines using Excel, Power BI, Python, and SQL. Experienced in documenting business requirements, mapping processes, and delivering structured analytical reports to support strategic decision-making across functions. IBM-certified with a proven record of improving reporting efficiency by 20-30%.
Sandip University, Nashik
BCA · Computer Applications
August 1, 2022 – June 30, 2025
PNS Corporate Services
MIS & Business Analyst - Reporting, Analytics & Process Improvement
May 1, 2025 – April 1, 2026
Nashik, Maharashtra, India
Supply Chain Performance & Risk Analytics
June 1, 2026 – Present
• Analyzed 172,765 orders, $35.2M revenue across 23 global regions and 37 months - performed EDA, data cleaning (7,754 records removed, 30 columns dropped), and feature engineering to surface operational bottlenecks and profitability trends • Conducted root cause and risk analysis across shipping modes, customer segments, and geographies; identified First Class shipping as a 100% delay failure tier and translated findings into a prioritized business action plan • Built a Random Forest ML model (73.8% accuracy, 0.82 ROC-AUC) to predict late delivery risk at order level, providing a data-driven, forward-looking analytical tool for supply chain decision-making • Prepared a fully structured management report documenting findings, variance commentary, process gaps, and phased recommendations - aligned with both data analytics and business analysis reporting standards
Global Superstore Sales Dashboard
June 1, 2026 – Present
• Collected and analyzed 10,000+ rows of sales, revenue, and profitability data across customer segments, product categories, and geographies to identify performance gaps, trends, and growth opportunities • Built interactive KPI dashboards with DAX measures (YoY growth, profit margin, sales velocity) and drill-through filters, enabling self-service analytics and reducing ad-hoc reporting requests from business teams • Defined business rules for all KPI calculations, validated outputs against source data, and delivered monthly and quarterly performance report packages with data-backed recommendations to stakeholders
Large-Scale Data Pipeline
June 1, 2026 – Present
• Engineered an automated ETL pipeline consolidating 150+ Google Sheets (3000+ tables) into a single structured reporting system, standardizing data workflows and significantly reducing manual data preparation time • Implemented automated validation and error-flagging logic to detect inconsistencies and enforce data governance standards across all data sources, ensuring clean and reliable outputs for downstream analysis • Documented pipeline logic, data flows, and business rules to support cross-team handoff, ongoing maintenance, and continuous analytical process improvement
IBM Data Science Professional Certificate
IBM
June 1, 2026 – Present
Data Analyst & Business Analyst Certification
Technokraft Solutions
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from supply chain analytics to sales dashboards and data pipelines, indicates adaptability and a broad interest in data-driven problem-solving. Their experience in a 'MIS & Business Analyst' role shows a blend of technical and business-oriented skills, which is a good fit for organizations valuing cross-functional collaboration and practical application of data insights. The certifications further demonstrate a commitment to continuous learning and skill development.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills such as stakeholder communication, critical thinking, attention to detail, cross-functional collaboration, problem-solving, and report presentation, which are crucial for a Data Analyst role. Their experience in process improvement and automating reporting aligns well with operational efficiency needs.