Data Analysis

Inspect, cleanse, and wrangle data; discover actionable information and patterns; communicating solutions that support business and marketing strategy.

Software Engineering

Professional experience developing software using a variety of languages; strong understanding of writing maintainable code using best practices and patterns.

Statistics and Machine Learning

Strong understanding of statistical/machine-learning concepts including p-value, tests, distributions, predictive modeling, clustering, and more.

A/B Testing

Running statistical experiments on websites/apps to produce data-driven decisions that lead to increase in customer value and conversion rates.

R Language

One of the most popular languages for data analysis and machine learning. Familiar with popular packages such as ggplot, dplyr, tidyr, caret, etc. that streamline analysis.

SQL

Data is often stored in databases like MS SQL Server or Amazon Redshift and has to be retrieve before it is analyzed. SQL is often the language used for retrieval.

General Tools

Demonstrated ability to quickly come up to speed and become proficient in many different tools, programming languages, and techniques.

Misc.

Python; C#; Java; Regular Expressions; JavaScript/JQuery; MS SQL Server; Redshift; Excel; Domo; Google Analytics & Tag Manager; Balsamiq Mockups