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San Jose, CA · Open to Bay Area & Remote
Seeking Data & Business Analyst Roles

Data that
drives decisions.

I'm Kyle — a recent SJSU grad (B.S. MIS, Summa Cum Laude) who turns messy datasets into clear strategy. I've analyzed half a million transactions, built automated pipelines, and shipped an AI-powered app.

Python · SQL · Tableau Analytics & Strategy Business Intelligence AI & Automation Operations & Process
KD
Kyle T. Dang
B.S. MIS · Summa Cum Laude · May 2026
500K+Records Analyzed
3.854GPA · Summa Cum Laude
4+Years in Healthcare Data
2,400+Meal Entries Built (Platify)
About Me

Hi, I'm Kyle.

KD

I just graduated from SJSU in May 2026 with a B.S. in Management Information Systems, finishing Summa Cum Laude with a 3.854 GPA. I grew up in San Jose and I'm looking to start my career as a data or business analyst somewhere in the Bay Area.

During school I looked for real experience wherever I could find it. Since 2022 I've been a volunteer healthcare data analyst at a local clinic — showing up regularly, analyzing patient vitals, and building Python scripts to automate reporting that used to be done by hand. I also spent a semester doing a systems and UX audit for a Salesforce platform that 300+ nonprofits use to manage volunteers. Both roles taught me how to work with real, messy data and communicate findings to people who aren't data people.

Outside of that, I've done several independent analysis projects — a churn prediction model, a Tableau sales dashboard, NBA matchup stats — and I'm currently building Platify, an AI meal recommendation app I started from scratch after graduating. I work in Python, SQL, Excel, and Tableau, and I've been getting into AI tooling (LangGraph, RAG, vector stores) through a course I took my final semester.

I'm a fast learner, I take feedback well, and I genuinely enjoy this kind of work. If you're looking for someone entry-level who's already put in the reps, I'd love to connect.

📍
LocationSan Jose, CA · Open to Bay Area
🎓
DegreeB.S. MIS, SJSU · Summa Cum Laude · May 2026
🎯
TargetingData Analyst · Business Analyst · Systems Analyst
Technical Skills

What I work with

Data & Analytics
Python SQL Tableau Pandas NumPy Matplotlib Seaborn scikit-learn Excel Pivot Tables
AI & Systems
LangGraph OpenAI API RAG FastAPI Vector Stores Salesforce CRM Claude AI React Native Supabase
Tools & Platforms
GitHub JupyterLab Google Colab Notion JavaScript Google Places API FatSecret API
Methodologies
Agile / Scrum SDLC ER Modeling ETL Pipeline UX Research WCAG 2.1 Logistic Regression Feature Engineering
Experience

Where I've worked

Healthcare Data Analyst
Dr. Kumo — San Jose, CA · Volunteer
Jun 2022 – Present
  • Analyzed vital data for 40–60 patients per session using Excel and Python to surface clinical trends and flag abnormal patterns for medical staff
  • Built automated Python reporting that replaced manual health summary workflows, reducing review time and improving consistency
  • Structured and maintained longitudinal patient datasets to enable accurate tracking of health trends over time
System Analyst & UX Consultant — ↗ GitHub
Santa Cruz County Volunteer Center — San Jose, CA · Volunteer
Aug 2025 – Dec 2025
  • Audited a Salesforce-based volunteer platform used by 300+ nonprofit partners, identifying key accessibility and usability gaps
  • Produced redesign documentation including wireframes, WCAG 2.1 improvements, and navigation restructuring
  • Delivered stakeholder-facing recommendations that aligned system changes with real user needs and scalability goals
Founder & Developer
Platify — AI Meal Recommendation App · San Jose, CA
May 2026 – Present
  • Building a React Native app that personalizes meal recommendations using live restaurant, nutrition, and AI APIs for users with dietary restrictions
  • Structured and managed 2,400+ meal entries across 140+ restaurant chains, with filtering logic for calories, allergens, and nutrition goals
  • Integrated Google Places, FatSecret, Supabase, and Claude AI APIs for real-time data — handling the full data architecture from ingestion to recommendation output
Projects

Selected work

Data Analysis Feb – Apr 2026
IBM Telecom Customer Churn Analysis

Built a predictive model to flag at-risk customers before they leave. Cleaned and engineered features from 7,043 records, ran EDA to surface the key churn drivers, then trained a logistic regression classifier — giving the business a tool to act on, not just a report to file away.

Month-to-month contracts had significantly higher churn than annual plans Fiber optic customers churned at 40%+ — highest of any service tier Electronic check users showed elevated risk; auto-pay users churned far less Customers without add-ons (security, support) were 2× more likely to leave
Python Pandas Seaborn scikit-learn ETL Pipeline Logistic Regression Google Colab
View on GitHub
Churn Rate by Contract Type
Month-to-Month
42%
Fiber Optic
41%
Electronic Check
36%
No Add-Ons
31%
Annual Contract
11%
7,043 customers
26.5% overall churn
5 risk segments
Business Intelligence Feb – Mar 2026
Online Retail Sales Dashboard

Turned 500K+ messy transaction records into an interactive Tableau dashboard that a non-technical stakeholder can actually use. The focus was storytelling — seasonality trends, top products, geographic revenue splits — presented so business decisions are obvious at a glance.

Revenue spiked sharply in Nov–Dec — inventory planning opportunity UK represented the majority of revenue, creating geographic concentration risk Small % of customers generated disproportionate revenue — high retention priority Gift and decorative items consistently outperformed other product categories
Excel Tableau Pivot Tables Data Cleaning KPI Dashboards
View on GitHub
Monthly Revenue Trend (Indexed)
Nov–Dec peak
JanMarJunSepNovDec
Revenue by Region
United Kingdom
82%
Europe (other)
12%
Other Markets
6%
AI Engineering Spring 2026 · SJSU BUS4 118S
Agentic AI — Automated IT Support System

Built a full agentic AI system that autonomously handles IT support workflows — from intake and intent classification to resolution and escalation. Led the team as project manager while also contributing to implementation.

AI agents handle password resets, software troubleshooting, and phishing detection end-to-end RAG with vector embeddings powers contextual knowledge retrieval for support responses LangGraph-style orchestration routes, escalates, and resolves tickets without human input Designed 3 full use-case workflow diagrams and a complete system architecture
Python LangGraph RAG Vector Stores Agent Orchestration Jupyter Notebook
View on GitHub
Agent Workflow — Ticket Resolution
Ticket Intake
Intent Classifier
RAG Retrieval
Agent Resolution
Escalation Check
Auto-Resolved
3use cases
RAGknowledge base
PM+ dev role
In Progress May 2026 – Present
Platify — AI-Powered Meal Recommender

Founded and built a React Native app that personalizes restaurant meal recommendations using live APIs and AI. Users input dietary restrictions, calorie goals, and allergens — Platify matches them to real menu items from 140+ chains in real time.

Structured 2,400+ meal entries across 140+ restaurant chains Integrated Google Places, FatSecret, Supabase, and Claude AI for live data Custom filtering and ranking logic for calories, allergens, and nutrition goals Full-stack: data architecture, API integration, and mobile UI
React Native Claude AI API Supabase Google Places API FatSecret API JavaScript
Data Architecture
Live APIs
Google Places FatSecret Claude AI
Database
Supabase · 2,400+ meal entries · 140+ chains
Ranking Logic
Calories · Allergens · Macros · Preferences
Exploratory Analysis Apr 2026
NBA Head-to-Head Performance Analysis

Exploratory data analysis of 2024–25 NBA game data to evaluate how player performance shifts depending on matchup. Cleaned raw game logs and surfaced statistical patterns across opponents.

Player performance varies significantly by opponent — matchup context matters Field goals and minutes played showed strongest correlation with game outcomes Built end-to-end: raw CSV ingestion, cleaning, EDA, and documented insights
Python Pandas Jupyter Notebook EDA Data Cleaning
View on GitHub
Performance vs. Opponent (Sample)
vs. Bottom-5
+28.4
vs. Mid-Tier
+24.1
vs. Top-10
+18.7
vs. Top-3
+14.2
24–25NBA season
EDAmethodology
Education

Academic background

San Jose State University
B.S. Business Administration — Management Information Systems
San Jose, CA · Conferred May 20, 2026
✓ GPA: 3.854 🏆 Summa Cum Laude ⭐ President's Scholar
Preview Unofficial Transcript
Relevant Coursework
Python SQL Database Management Systems Systems Analysis & Design Networking & Data Communications Business Analytics Statistics MIS Practicum Cybersecurity Systems Mgmt Financial Accounting Operations Management Strategic Management Agentic AI
3.854 Final GPA
Summa Cum Laude
Contact

Open to analyst roles
in the Bay Area

I'm actively looking for data analyst, business analyst, and systems analyst opportunities. If you think I'd be a fit, I'd genuinely love to hear from you.

Kyle T. Dang · San Jose, CA · 2026

KyleDang14@gmail.com