Sumedha Uppal | Portfolio

Education

Bachelor of Science in Computer Information Technology | Expected Graduation: Spring 2026

GPA: 3.71
Honors: Dean's List (6 semesters) | Associated Students Scholarship Recipient
Leadership: Vice President of Finance, Management Information Systems Association – Managed $5K budget and reduced reconciliation time by 40% using Power BI dashboards

Power BI (Certified), Tableau, SSRS, Advanced Excel (PivotTables, Power Query, Data Modeling)

SQL (MySQL, SSMS, BigQuery), Python (Pandas, NumPy, Scikit-learn), ETL/ELT, Data Cleaning

Google BigQuery, AWS, Amazon Redshift, CRM Systems, Azure DevOps, ERP Systems, Vertex AI, Salesforce

Campaign Performance Tracking, Account-Based Marketing (ABM), Customer Segmentation, Predictive Analytics, A/B Testing, RFM Analysis

CSUN Institute for Sustainability | Northridge, CA | Sept 2024 – Present

Engineered Python-based data preprocessing pipelines to clean and validate 200+ complex records, increasing data quality by 32% and eliminating 12 hours of manual work weekly.
Created SQL-driven analytical reports and documentation supporting data-driven presentations for 6 regional conferences and university stakeholders.
Implemented automated validation scripts that reduced historical reporting errors by 18%, ensuring data integrity for strategic initiatives.

SANDAG | San Diego, CA | Apr 2025 – Jul 2025

Designed and deployed 8+ interactive Power BI and SSRS dashboards, reducing cross-departmental reporting cycle by 45% and enabling data-driven decision-making for 30+ operational teams.
Built SQL-based data transformations and canonical views for enterprise datasets, centralizing critical reporting logic and improving data accessibility.
Developed automated C#/.NET data pipeline reducing manual processing time by 35% while maintaining 100% accuracy for financial records.

TeleWorld Solutions, Inc. | Remote | May 2024 – Aug 2024

Developed Python anomaly detection framework analyzing performance metrics across 100+ network entities, increasing root-cause identification efficiency by 25%.
Built executive-level Power BI visualizations translating technical performance data into actionable insights for cross-functional leadership teams.
Reconciled data discrepancies between legacy and modern systems, improving overall reporting reliability by 20%.

Jupyter Notebook Python SQL DuckDB

Developed an interactive decision-tree pruning playground (pre/post pruning) with SQL feature engineering in DuckDB.
Integrated Plotly widgets and deployed the application as a shareable Streamlit app.

Jupyter Notebook Python Machine Learning

Built a predictive machine learning model to estimate housing prices based on property features and historical data.
Performed data exploration, preprocessing, and model evaluation utilizing Jupyter Notebooks and Python libraries.

Python Data Analysis

Developed a Python-based project aimed at analyzing and predicting patterns in food waste.
Implemented data-driven techniques to provide insights on food consumption and waste reduction strategies.