James Dargan

**** ********* *** * adkmso@r.postjobfree.com http://linkedin.com/in/jamesdargan/

Seattle, WA 98103 817-***-**** http://jamesdargan.github.io I am a problem solver, leveraging data collection, statistical analysis, and predictive modeling skills to solve complex business questions. I bring management experience, exceptional communication skills, and a passion for data-driven business decisions to my analysis on behalf of WaferWire’s client seeking a Data Scientist 1. Technical Skills

SQL – Joins, CTE’s, Subqueries, Window Functions, Indexes; Microsoft Office – Word, Excel, PowerPoint Python – Data Collection & Cleaning, Visualization, Modeling (pandas, statsmodels, scikit-learn, seaborn, plotly) Statistics: - Hypothesis Testing; AB Testing; Experimental Design; Parametric and Non-parametric Models Data Science: - Exploratory Analysis; NLP; Model Optimization; Forecasting of KPIs; Dashboard Design Education

Certificate, Data Science Immersive March 2020 – June 2020 General Assembly, Seattle, WA

Mastered Python to execute applied data science projects end-to-end including data collection and cleaning, data visualization, statistical analysis, and modeling with machine learning algorithms. Delivered presentations translating complex analysis for non-technical stakeholders with actionable business insights. Bachelor of Arts, Mathematical Economical Analysis (GPA: 3.7/4.0) August 2011 – May 2015 Rice University, Houston, TX

Graduate-level Coursework: Mathematical Statistics / Probability, Linear Statistical Models, Simulation Modeling Data Science Projects

Forecasted Walmart Store Sales to Inform Resource Allocation

• Model: Optimized SARIMA time-series model with historical sales data over 45 Walmart stores to forecast sales demand 3 weeks ahead with a rolling window MAPE of 6.08 percent.

• Takeaway: Improved baseline performance by 50% enabling more accurate staff planning and allocation. Participation Rate Bias in ACT and SAT State Averages to Inform Class Size Optimization

• Model: Predicted ACT averages with MAE of 0.75 points using OLS regression after feature selection.

• Takeaway: Demonstrated how failing to identify bias source produces flawed inference about features. After controlling for bias, showed test scores increase with smaller class sizes and higher paid teachers. Subreddit classification of /r/pcgaming and /r/boardgames subreddit

• Model: Grid-search optimized 3 NLP bag-of-word models with increasing scope of text input.

• Takeaway: Demonstrated peak accuracy of 98% cost 7x computational resources of 90% accuracy model. GA Kaggle for AMES Housing Prices Regression Model Challenge to Improve Profitability

• Model: Built Voting Regressor weighing OLS, RF, and XGBoost models to produce a RMSE of $18,320, a 60% improvement from baseline and 20% improvement from best OLS model with engineered features.

• Takeaway: Improved profitability by delivering realistic selling price estimates via ensembled models. Work Experience

Data Analyst (Volunteer) July 2020 – September 2020 Mary’s Place, Seattle, WA

• Collaborated in team of 4 to quantify client demographics and disparities in client service utilization. Team Lead June 2018 – March 2020

Uline, Lacey, WA

• Initiated and implemented novel proposals to deliver labor-saving process improvement initiatives. o Optimized carrier door assignments in dock to reduce forklift loaders’ travel by 5%.

• Implemented audits and researched error root causes to drive my 20+ staff team above 99.95% accuracy.

• Coordinated outbound trailer pickups across 6 logistic providers totaling 60+ pickups daily.

• Managed Sunday production shift, balancing labor across 3 departments and beat 30 min OT goal.

• Owned KPI reports for my team, creating action plans to meet business objectives on weekly basis.