I currently lead Remind's Data team, which includes data engineering, data analytics, and data science. Data at Remind supports all of our business areas and functions, which are our SaaS messaging platform sold to educational organizations, our direct-to-consumer online tutoring marketplace, and our core capabilities and infrastructure. I report directly to the CEO.

Highlights thus far include:

• Building out the team, growing from 3 to 7 while creating sustainable processes for team planning, coordination, and collaboration.
• Working closely with executives and cross-functional stakeholders like product, engineering, and go-to-market to identify needs, build roadmaps, and execute on them.
• Analyzing and reporting on product usage and the impact of new features, such as analyzing the nuanced but overall positive impact of a shift to an "opt out" subscription model in our direct-to-consumer tutoring product.
• Investigating drivers of key business outcomes, such as identifying several factors that cause users to be less likely to convert into a paid customer that once addressed would improve paid conversion by 10-15%.
• Improving our data processing architecture, speeding up our end-to-end batch processing time by over 5 hours each day and reducing the effort needed to create new pipeline jobs.

I was an architect and lead developer for Samba's data licensing products, helping them improve and scale those products from <$1m to $XXm ARR. This involved a variety of data science and engineering approaches, including but not limited to:

• Spearheading the use of TV labs for rigorous and ongoing evaluation of our methodologies and as a platform for evaluating future changes, enabling us to roll out the first major improvement in out content recognition technology in several years and improving overall accuracy by more than 25%.
• Using natural language processing techniques to identify similarity and disagreements between Samba's internal data and third party data, improving accuracy of ad metadata by more than 50%.
• Designing, creating a proof of concept, and leading cross-functional implementation of a system to forecast household-level viewership.
• Working closely with cross-functional groups such as sales, product, engineering, and executives on defining team and company roadmaps.

I also led data science interviewing and was very hands-on in mentoring data scientists and analysts on my team on technical and non-technical aspects of their jobs.

I contributed to and managed a variety of data science projects and teams at Allstate:

• Generating predictive insights for Arity's consumer products. This involved working with a cross-functional team of user research, design, engineering, and project management to scope, build, and implement predictive models that created user value.
• Personalizing Allstate’s interactions with their customers, focusing initially on consumer marketing but expanding to other business areas.
• Developing internal software packages to make data science work more efficient and accurate, including data exploration and model implementation.
• Building and implementing a variety of models within Allstate's life insurance group, including underwriting, payment patterns, and retention.

I worked primarily in R, Unix, Hive, Spark, SQL, and Python. I also led data science interviewing within Allstate's centralized data science group.

I helped our clients make smarter decisions by better understanding and utilizing their data. This involved a mixture of individual work and leading others on projects. I worked primarily in R.

Examples of projects that I worked on:

• Segmenting 45,000 products based on their historical sales performance in order to better predict sales performance of new products. Improved future supply management and planning of promotional incentives for the holiday shopping season.
• Developing a prospect scoring system on 5 million potential customers using 360 demographic and psychographic characteristics. Estimated to improve prospect targeting by 300% compared to random mailing.

I designed, built, and monitored automated file processes for Wells Fargo's prospect and customer databases using Unix and SQL.

My accomplishments included:

• Preventing 20 hours of lost processing time each month by troubleshooting processing errors.
• Receiving awards for training business analysts and helping onboard a new client.

Earned a department fellowship with a curriculum focused on data mining.

Graduated Summa Cum Laude from the UCA Honors College.