Available for opportunities

Hi, I'm Michael Tucker Data Analyst

I turn messy data into clear decisions — drawing on a background in fraud detection, operations, and customer support to deliver analysis that actually matters.

0K+
Records analyzed
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Portfolio projects
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Industry domains
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About Me

An analyst forged at the intersection of data, operations & trust

Before I ever opened a Jupyter notebook, I was deep in the weeds of operations — tracking queues, spotting inefficiencies, and learning how organizations really work. Then customer support taught me to read between the lines of what customers say versus what the data shows. Fraud work sharpened my instinct for anomalies and trained me to think adversarially.

That combination — operational realism, customer empathy, and a fraud analyst's skepticism — makes me a different kind of data analyst. I don't just clean data and build charts. I bring context that most analysts lack, because I've lived in the very systems I'm now hired to analyze.

I'm currently seeking junior analyst roles where I can contribute immediately while continuing to grow. I work in Python, SQL, Excel, and Power BI — and I'm deeply motivated by problems that affect real business outcomes and real people.

⚙️
Operations Process analysis · KPI tracking · Workflow optimization
🎯
Customer Support Ticket intelligence · CSAT analysis · Resolution metrics
🔍
Fraud Analytics Anomaly detection · Pattern identification · Risk scoring
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Status Open to Work
Primary Tools Python · SQL · Power BI
Looking for Analyst Roles · Remote Friendly

Technical Toolkit

The stack behind
the analysis

Core Technologies

Python SQL Excel (Advanced) Power BI Tableau Git / GitHub

Python Libraries

Pandas NumPy Matplotlib Seaborn Scikit-learn

Domain Expertise

Fraud Detection Operations Analytics Customer Experience Risk Analysis

Analytics Methods

EDA Data Cleaning Statistical Analysis Predictive Modeling Cohort Analysis A/B Testing
92% Fraud detection precision achieved in project
500K+ Records analyzed across portfolio projects

Portfolio

Work that speaks
for itself

Real analyses. Real code. Documented results.

02

Google Data Analytics Capstone

Capstone project for the Google Data Analytics Professional Certificate. Applied the full analysis workflow — ask, prepare, process, analyze, share, act — to a real-world business scenario, producing actionable recommendations backed by clean, reproducible Python analysis.

  • End-to-end analysis from raw data through stakeholder deliverable
  • Data cleaning, transformation, and exploratory analysis in Python
  • Findings visualized and summarized in a professional presentation
Python Pandas Matplotlib Seaborn
03

Dr. Semmelweis Handwashing Analysis

Replicated and extended the landmark 19th-century analysis by Dr. Ignaz Semmelweis, whose handwashing data saved lives — and whose findings were dismissed for decades. Used R to run the same statistical tests and visualize why the data was so compelling, and so tragically ignored.

  • Time-series analysis of mortality rates across two hospital clinics
  • Bootstrap hypothesis testing to quantify the handwashing effect
  • Historical data storytelling — making century-old numbers speak clearly
R ggplot2 dplyr tidyverse
04 Python Basics

Number Guessing Game

A Python CLI game demonstrating foundational programming skills — control flow, functions, input validation, and user feedback loops. Clean, well-structured code.

Python

Contact

Let's build something
worth analyzing

I'm actively looking for analyst opportunities. Whether you have a role, a project, or just want to talk data — my inbox is open.