Luke Edwards

Luke Edwards

Data Science & Analytics Professional

 

I'm a data scientist who loves solving the puzzle that data brings, discovering the "why?" behind every new problem. Whether it's building predictive models, running experiments, or automating workflows with Python, I enjoy solving problems that matter. I got my start in economics, sharpened my skills in analytics roles, and now focus on making data science both practical and impactful. I used to be a collegiate basketball and collegiate esports player, now I channel that same focus and drive into tackling tough data challenges.

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Projects

Explore my data science work
AI-Powered Earnings Sentiment Analysis & Investment Research Platform
NLPGPT-4Python

AI-Powered Earnings Sentiment Analysis & Investment Research Platform

Built an NLP pipeline combining GPT-4 and machine learning to link earnings call sentiment to subsequent stock performance, with a conversational interface for querying insights across filings.

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Counter-Strike Match Outcome Predictor
Machine LearningEsports AnalyticsPython

Counter-Strike Match Outcome Predictor

Developed an ML model predicting esports match outcomes from team performance metrics and map history, simulating best-of-three series to estimate win probabilities.

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Why Prime Members Stay: A Deep-Dive with XGBoost
Machine LearningPythonDecision Trees

Why Prime Members Stay: A Deep-Dive with XGBoost

Built and tuned XGBoost, Decision Tree, and Random Forest models to predict subscription behavior and identify key drivers of customer retention.

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Stopping Turnover: A Decision-Tree Churn Risk Analyzer
ClassificationHR AnalyticsPython

Stopping Turnover: A Decision-Tree Churn Risk Analyzer

Developed a decision tree model with 95.9% accuracy to identify employees at risk of leaving.

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Three Decades of Mental Health: Regression Reveals the Story
RegressionTime SeriesR

Three Decades of Mental Health: Regression Reveals the Story

Explored 30 years of global mental health data from 101 countries using multivariate regression to uncover key trends and patterns.

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From ’80 to Today: Modeling NBA Win Chances
Sports AnalyticsRegression Modeling

From ’80 to Today: Modeling NBA Win Chances

Analyzed 40 years of NBA data to find the key factors that influence team success, using statistical methods and regression analysis.

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Product launch Power BI dashboard
Power BIDAXSQL

Product Launch Performance (Power BI)

KPI cards and region drilldowns (orders, activations, invoice status) with DAX measures & scheduled refresh—used by sales/ops to track rollout in near real time.

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Excel dashboard of video game sales
ExcelPivot TablesVisualization

Video Game Sales Dashboard (Excel)

Interactive Excel report with slicers and pivots: top genres/publishers, year trends, and platform comparisons for quick executive reads.

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Skills

The tools and techniques I work with

Programming & Data Tools

Python SQL Git / GitHub Databricks Snowflake Claude Code

Machine Learning

scikit-learn XGBoost LightGBM SHAP

Data Engineering & Cloud

ETL Pipelines DAX

Visualization & Statistics

Power BI Tableau Matplotlib Hypothesis Testing Experimental Analysis Regression Analysis

Experience & Education

My professional journey

Data Scientist

Veterans United Home Loans | January 2026 - Present

  • Built diagnostic Tableau dashboards for the company's highest-volume product, replacing ad-hoc SQL triage and enabling 1,000+ employees to self-serve activity investigations across millions of lead-level records
  • Designed score-based Hot/Warm/Cold routing tiers for 500,000+ leads by operationalizing an existing ML model in Python and Snowflake, surfacing a top segment (14% of leads) with a 1.7x close-rate lift
  • Trained a decision tree to extract interpretable routing rules from the model, giving operations teams transparent criteria in place of opaque scores
  • Designed AI-assisted workflows and reusable Python tools that automate recurring analyses across product and ops stakeholders

Data Scientist

CIBT | May 2025 - September 2025

  • Developed a Python-based ML model to explain NRPU fluctuations by product and region using SHAP values, reducing manual variance analysis by 90%
  • Engineered AI prompts in OpenAI to automate lead-sourcing research, reducing manual marketing effort by 70%
  • Built fully automated Power BI dashboards to track commissions; designed filtering and revenue logic, enabling near-instant payout validation
  • Delivered weekly insights and trend breakdowns to leadership, accelerating decision-making across multiple business lines

Data Scientist

Independent Consulting | August 2024 - January 2025

  • Engineered Python data pipelines integrating social media APIs to automate collection and cleaning of engagement metrics, replacing manual data pulls for a media client
  • Delivered ongoing performance reporting and analysis that gave the client continuous visibility into content engagement trends

Google Advanced Data Analytics Professional Certificate

2024

Statistical analysis, ML fundamentals, predictive modeling, and data-driven decisions in Python.

Senior Business Intelligence Analyst

CIBT | July 2023 - April 2024

  • Standardized enterprise-wide reporting, reducing redundant metrics by 60%
  • Built KPI-driven Power BI dashboards, providing executives with real-time performance views
  • Rewrote and optimized SQL queries to cut reporting load times by 43%
  • Partnered with data engineers to develop DAX logic and integrate Snowflake pipelines, improving accuracy and scalability

Senior Financial Analyst

Interface Financial Group | June 2022 - May 2023

  • Automated client analysis with Python, reducing processing time by 93% (20+ hours/month saved)
  • Conducted credit risk and investment evaluations for small business clients, supporting multi-million-dollar funding decisions
  • Integrated data-driven logic into underwriting, improving portfolio quality

Master of Economics

Boise State University

Specialized in Econometrics, Statistical Analysis, and Machine Learning.

Bachelor of Science in Economics

University of La Verne

About Me

My journey in data science

I grew up obsessed with solving problems, breaking down tricky boss fights in video games, strategizing with teammates in basketball, and later, making sense of messy data.

Those habits pulled me toward economics and then applied data science, where I learned to use statistics and machine learning to tackle real business challenges.

Since then I've automated client analysis, built predictive models, and designed an NLP pipeline that extracts insights from SEC earnings calls. Every project is a new puzzle to solve.

As a former college athlete, I bring collaboration, focus, and constant iteration to every role and project.

Recently, I built a model to predict professional match outcomes in Counter-Strike 2 (CS2), a title with 1M+ concurrent players each month.

Get In Touch

I'm currently looking for data science opportunities...

Email luke3dwards32@gmail.com LinkedIn Connect with me GitHub View my repositories