Sep 2023 – Present · 2 yrs 8 mos · San Jose, CA · Remote

• Founded and scaled an AI-first marketing services firm to serving 20+ clients ranging
• from small businesses to companies above $10M ARR.
• Delivered 15 websites, 5,000+ social posts, and 100+ ad campaigns, while building analytics to track lead flow and CPA performance across accounts.
• Built internal AI automations and custom tooling for deep research, SEO, and review management, accelerating
• execution and improving campaign consistency.
• Built a proprietary social media operations platform (social.silvermine.dev) and led a 7-person team across social, paid media, SEO, and website delivery.

Jan 2023 – Mar 2024 · 1 yr 2 mos · San Francisco Bay Area · Hybrid

• We're a fast-growing startup helping business understand the impact of their marketing spend through multi-touch attribution (MTA) and other methods.
• Building a machine learning/AutoML platform to generate automated budgeting insights for our clients.
• Data engineering, ML engineering, etc.

Feb 2022 – Dec 2022 · 10 mos · Remote

• Driving growth in hotel bookings on the Hopper app.
• Recommenders, predictive modeling, pricing, business analytics, data quality, online experiments (A/B or split testing).

Apr 2021 – Feb 2022 · 10 mos · San Bruno, California, United States

• Improved music recommendations through online experimentation and causal inference

Mar 2020 – Apr 2021 · 1 yr 1 mo · Mountain View, California, United States

• Google Maps: Trends, metrics, and user-insights for user-generated content (photos, reviews, ratings, etc.).

Jun 2018 – Mar 2020 · 1 yr 9 mos

• I focus on big data and machine learning, building credit decisioning models, and working alongside business partners to push to market data-driven analytical solutions. I am an end-to-end data scientist: I build software that queries billions of rows of data from relational databases, uses Spark to process data sets, and trains machine learning models. I build interactive dashboards to analyze and compare model iterations and monitor model performance. And I do all of that in the cloud.
• Tools:
• Languages: Python, Apache Spark (SQL, pyspark), h2o.ai, R, R Shiny (dashboard)
• Platforms: AWS (Redshift, S3, EMR, EC2), Databricks, Linux
• Other: git, GitHub, bash, Agile, Vim
• Machine Learning: Logistic regression, gradient boosted machines (GBM), decision trees

Jul 2017 – Jun 2018 · 11 mos

• Built end-to-end data engineering and machine learning pipeline (ETL). Extracted two billion rows of transactional, payment, and credit history from 17 disparate data sources and combined into a single, model-ready dataset.
• Built cloud infrastructure to perform distributed computing, hyperparameter tuning, and big-data machine learning models.
• Influenced stakeholders on business strategy using data and modeling results.
• Identified, introduced and developed new technologies, influencing the business and technology startegies of the team.

Aug 2016 – Jul 2017 · 11 mos

• Working alongside industry experts, I perform rigorous data analysis to provide economic damages estimates in high-stakes litigation. I help transform raw data from disparate data sources into simple insights for colleagues, partners, and clients. I work primarily in the pharmaceutical and financial industries.
• Developed 50+ VBA tools from scratch into an Excel Add-in that saves colleagues five hours each month.
• Developed a fully-responsive RShiny Web Application to visualize predictive models.
• Forecasted interest rates using 13,000+ dynamic forecasting OLS models in Stata.
• Created a reactive Excel VBA dashboard to assess performance and accuracy of regressions.

Aug 2015 – Aug 2016 · 1 yr

• Pulled and processed financial metrics of 200+ companies and performed fixed-effects regression (S&P Capital IQ data and Stata).
• Investigated generic drug entry effects on brand revenues. Automated the production of a several hundred charts, and dozens of presentations using VBA, Excel, and PowerPoint.
• Webscraped using Python, visualized data using R, and forecasted time-series events using Matlab and Stata.

May 2013 – Aug 2013 · 3 mos · Greater Salt Lake City Area

• Conducted market research on corporate debt instruments, modeled mortgage-backed securities, and presented buy-sell decisions weekly to management.
• Analyzed corporate financials and complex legal prospectuses to assess credit worthiness of debt investments.
• Used innovative techniques to assess prediction accuracy of mortgage-backed security forecasts.
• Applied financial theory, such as time-value of money, bonds, and structured products to the analysis of MBS tranches, waterfalls, trustee reports and modeled cash flows.
• Presented research, market insights, and credit reports on a weekly basis to the Chief Investment Officer.

Jan 2013 – Sep 2014 · 1 yr 8 mos · Provo, Utah Area

• Endeavored to change how the world accesses home security. Focused on creating disruptive innovations to simplify home security without contracts, call centers, or monthly fees.
• Worked with cross-functional teams to transform a raw, innovative idea into a funded business.
• Tested product development hypotheses door-to-door with potential customers.
• Sold over 1200 units to 850 customers in 30 days, finishing in the top 2% of all Kickstarter projects.
• Analyzed 200 customer survey responses to extract insights and understand product price sensitivity.
• Pitched key business ideas to angel investors, VCs, and PE investors and raised a seed round investment.

Sep 2012 – Apr 2015 · 2 yrs 7 mos · BYU

• Coordinated with local bank to identify and explain customer trends.
• Modeled debit card overdraft behavior using actuarial, zero-adjusted, and generalized linear models.
• Challenged government understanding of low-income consumers.

Sep 2012 – Aug 2013 · 11 mos · Provo, Utah Area

• Worked alongside Dr. H. Dennis Tolley in performing rigorous statistical analyses in matters of Medicaid pharmaceutical litigation and national defense consulting.
• Queried a relational healthcare database using SQL.
• Sampled a multi-million record database using stratified and matched-pairs sampling.
• Developed rapid detection methods with decision-tree algorithm for airborne bacteria using GC/MS data.

Jun 2012 – Aug 2012 · 2 mos · Greater New York City Area

• Financial Instrument Valuation team, the Deloitte advisory branch designated to price securities.
• Extracted pertinent information from original deal offering documents.
• Preformed pricing requests through Bloomberg Terminal.
• Validated vendor security information through extensive Bloomberg Terminal research.
• Demonstrated teamwork through effective communication and collaboration with co-workers.

Aug 2009 – Aug 2011 · 2 yrs · Tegucigalpa, Honduras

• Responsible for financial management and oversight of a 180-person organization.
• Involved in missionary service, teaching personal welfare principles and engaging in humanitarian service.
• Managed, instructed, and trained teams of 20 missionaries.