Philadelphia, PA · Open to Business Analyst, Data Analyst and BI roles

Auspicious Munemo

Business and Data Analyst turning raw data and stakeholder needs into dashboards, queries and recommendations teams can act on.

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  • Business Analyst
  • Data Analyst
  • BI / Power BI
  • SQL
  • Python & R
0concurrent client projects documented in Jira (Agile/Scrum)
0productivity gain from LLM-based workflow automation
0revenue increase contributed to through sales analytics insights
0GPA in the MS in Business Analytics at Drexel LeBow

About

Analytics that ends in a decision

I'm a Business Analyst and Data Analyst who applies business intelligence, cloud computing and automation to deliver measurable results.

My work spans requirements gathering, SQL analysis, Power BI dashboards and UAT across cloud-based client projects, plus sales and customer analytics in Zimbabwe. I'm completing a Master of Science in Business Analytics at Drexel University's LeBow College of Business (expected March 2027), after a BSc in Business Administration from the University of Zimbabwe.

Clarify business needs

Requirements, user stories and acceptance criteria that turn stakeholder asks into clear work items.

Turn data into decisions

SQL and Power BI reporting that answers the real business question for operational and executive audiences.

Automate the routine

LLM and agentic workflows that remove repetitive administrative work and free up team time.

Projects

Work you can open and inspect

SQL · Database design

Car Rental Service Relational Database

Which vehicles earn their keep, which customers come back, and where is payment risk building up?

A relational database in Oracle APEX modeling the full reservation-to-payment lifecycle across five entities: Customer, Vehicle, Reservation, Rental and Payment. Multi-table SQL answers three business questions on fleet utilization, customer retention and payment risk.

  • Oracle APEX
  • SQL
  • Data modeling
View on GitHub ↗
Generative AI · Agents

SmartShoe Generative Agentic AI

Can coordinated AI agents fix operational friction in a retail organization?

A multi-agent generative AI prototype built on Stack AI for SmartShoe. It turns business requirements into automated workflows, streamlines data exchange and supports automated decision-making. Reliability was tested with structured prompts, and agent decision paths were analyzed.

  • Stack AI
  • Multi-agent systems
  • Prompt testing
View on GitHub ↗

More work on GitHub

Browse repositories, code and write-ups for my analytics and AI projects.

View my GitHub ↗

Career

Experience

  • Documented business requirements, workflows, reporting solutions, user stories and acceptance criteria in Jira across Agile/Scrum sprints for 5+ concurrent client projects.
  • Led cloud-based project teams using AWS, Azure and GCP from initiation to closure, improving team workflows by 70-80%.
  • Queried company relational databases with SQL to analyze cloud projects, assignments and resource utilization.
  • Supported UAT by validating system outputs and identifying defects before release, improving deliverable quality by 80%.
  • Built and maintained Power BI dashboards tracking project KPIs for operational, departmental and executive reporting.
  • Co-designed scalable LLM automation workflows that removed routine administrative tasks, improving productivity by 70%.
  • Cleaned, validated and organized raw sales data in Advanced Excel; built Power BI dashboards with KPI reporting that helped leadership prioritize highest-margin products and optimize customer segmentation.
  • Contributed to a 50% revenue increase through data-driven insights that guided sales strategy and customer segmentation.
  • Wrote and optimized SQL queries to extract, validate and reconcile customer data, improving reporting accuracy by 60%.
  • Ran market research and competitor analysis that guided a digital advertising campaign, increasing customer engagement by 70%.
  • Developed Power BI dashboards visualizing customer engagement across digital platforms, cutting reporting time by 50%.
  • Analyzed purchase trends and product performance with Excel pivot tables, charts and KPIs, improving targeted sales planning by 30%.
  • Drexel University, LeBow College of Business: MS in Business Analytics, GPA 3.83, expected March 2027.
  • University of Zimbabwe: BSc in Business Administration, GPA 3.60, September 2024.

Certifications

Toolkit

Skills, with the work that proves them

Analytics, BI and cloud
  • Power BI
  • Tableau
  • Python
  • R
  • Advanced Excel
  • Jira
  • Azure
  • AWS
  • Google Cloud Platform
  • Qualtrics
  • Supabase
  • PowerPoint
Data and analysis
  • SQL (MySQL Workbench, PostgreSQL)
  • Data cleaning & validation
  • Data visualization
  • Statistical analysis
  • Predictive analytics
  • Machine learning
  • Generative AI
  • KPI reporting
  • Data modeling
Business analysis
  • Requirements gathering
  • BRDs
  • User stories & acceptance criteria
  • Process mapping
  • Stakeholder management
  • Agile/Scrum
  • UAT

Résumé

Read it here or take a copy

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