Business & Data Analyst - Analytics, QA, Product Insights

CONTACT

Portland, OR

503-***-****

************.*****@*****.***

SKILLS

Business Analysis

Data Analysis (SQL, Excel, Python)

Data Visualization (Power BI,

Tableau)

Stakeholder Management

Agile/Scrum

KPI & Metrics Design

A/B Testing

Data Validation & QA

ETL & Data Pipelines

JIRA, Confluence

Product Analytics

Process Optimization

EDUCATION

MS IT – St. Francis College

B.Tech – Andhra University

MOHAN SURYA GOWTHAM JADDU

Professional Summary

Business & Data Analyst with expertise in analytics, product insights, and quality engineering. Experienced in driving data-informed decisions, optimizing processes, and improving system reliability. Strong background in SQL, dashboards, experimentation, and stakeholder communication. Proven ability to deliver measurable impact in Agile environments. Professional Experience

Web Analytics & QA Consultant Quadar Systems

• Improved data tracking accuracy by ~25% by implementing validation frameworks and debugging analytics pipelines

• Partnered with product and business teams to translate requirements into data insights, accelerating decision-making cycles

• Designed dashboards and reports improving KPI visibility and stakeholder adoption by ~30%

• Reduced reporting inconsistencies by standardizing event tracking and QA processes

• Led cross-functional collaboration across analytics, engineering, and product teams

Digital Analytics & QA Analyst HCL Technologies

• Analyzed large datasets to identify trends and improve product performance metrics

• Increased reporting efficiency by ~30% through automation and dashboard creation

• Supported Agile delivery by refining requirements and validating business logic

• Reduced defects and improved system reliability via end-to-end testing and QA strategies

• Delivered actionable insights influencing product and operational decisions Projects

• Product Analytics Dashboard: Built KPI dashboards to track user engagement and conversions

• A/B Testing Analysis: Evaluated feature changes to optimize user experience and conversion rates

• Data Pipeline Validation: Ensured data accuracy across ETL workflows

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