Data Analyst - Pricing & Forecasting Insights
Resume:
MEGHNA SHAW
SKILLS
PROJECTS
• YipitData - Data QA Associate
EDUCATION
• ITC Infotech - Associate IT Consultant
• ReleaseMyAd - Product Management Intern
PROFILE SUMMARY
• IIT ISM Dhanbad
MBA, Business Analytics
• Dr B C Roy Engineering College, Durgapur
B Tech, Electronics & Communication Engineering
Jan 22- Jun 23
Gathered and analyzed business requirements, translating them into structured workflows and system solutions. Performed data validation using Python to support Manufacturing Execution System (MES) applications. Collaborated with stakeholders and cross-functional teams to ensure smooth implementation of operational processes. Identified system issues, conducted root cause analysis, and recommended process improvements. Supported project execution by aligning business requirements with technical solutions and validating system functionality. Contributed to digital transformation initiatives by improving process visibility, workflow efficiency, and data-driven reporting. May 2025
July 2021
May 24- Oct 24
Jun 25- Present
Workforce Attrition Analysis & KPI Dashboard: Github 1.Built an interactive HR Attrition Dashboard in Excel analyzing 2925 employees across 20+ variables using PivotTables, slicers & KPIs. 2.Identified a 28.3% attrition rate and high-risk segments like overtime employees and frequent travelers. 3.Delivered executive-ready insights across 3 departments & 5 education levels to drive data-backed retention & workforce planning. AI Hiring Assistant: Website
1.Built an AI-powered resume screening system using Word2Vec embeddings and cosine similarity. 2.Automated candidate-job matching, reducing manual effort and improving hiring efficiency. 3.Enabled intelligent semantic comparison beyond keyword-based filtering. Sentiment Analysis App: Website
1.Developed a real-time sentiment analysis app using Hugging Face Transformers and Streamlit. 2.Classified text into sentiment categories with confidence scoring. 3.Demonstrated practical application of Gen AI in text analytics and decision support. Programming & Querying: Python (Pandas, NumPy), SQL (MySQL, SQL Server, Window Functions), Regex. Data Operations & Analytics: Data Quality Assurance, Data Validation, Data Extraction, Data Cleaning, Data Labeling, Data Mapping, Product Attribution, Product Categorization, Data Analysis, Vendor Data Analysis, Anomaly Detection, Data Integrity, Data Governance Data Analysis & Visualization: Power BI (DAX, Power Query), Advanced Excel (Pivot Tables, VLOOKUP, Data Validation). AI/ML & Analytics: Machine Learning, NLP, LLM Basics, Predictive Analytics, A/B Testing, Exploratory Data Analysis (EDA), Data Transformation
Tools & Technologies: Git, Apriso, Google Workspace (Docs, Sheets, Slides), Microsoft Office Suite Business & Analytical Skills: Requirement Gathering, Business Rule Validation, Problem Solving, KPI Tracking & Reporting. GPA: 8.01/10
GPA: 8.43/10
WORK EXPERIENCE
GitHub +918********* Portfolio
Data Operations and Analytics professional with 2.5 years of experience in data quality assurance, SQL, Python, workflow automation, and cross-functional execution. Experienced in validating large-scale datasets, improving data accuracy, automating quality checks, and supporting product categorization through structured business rules. Skilled in data mapping, data validation, process optimization, stakeholder collaboration, and delivering high-quality analytical outputs in fast-paced environments. Passionate about leveraging data to improve operational efficiency and customer-focused product intelligence. Executed end-to-end data quality assurance on 65K+ records/week through anomaly detection and systematic audits, achieving ~83% accuracy, directly reducing downstream reporting errors that could skew client-facing market signals. Identified root causes of inconsistencies, resolving 76% issues proactively before downstream impact. Automated QA workflows through Python scripts and advanced SQL queries, improving efficiency by 37%. Validated vendor and merchant classification logic against business rules, improving reporting quality by 23%, enabling more accurate competitive benchmarking for clients.
Created QA documentation, validation checklists, and SOPs, reducing onboarding time for new team members by 18%. Collaborated with US & China teams to define QA standards, ensuring uniform data governance practices. Strengthened data integrity controls, maintaining zero critical production-level data failures. Analyzed business workflows to identify operational gaps and improve overall process efficiency Collaborated with product, operations, marketing, and tech teams to align execution with business goals. Tracked key performance indicators to evaluate performance and support decision-making. Conducted root-cause analysis to resolve bottlenecks and improve workflow effectiveness. Supported planning and execution of operational initiatives through data-backed insights.
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