Braden Jones Email and Phone Number

Enable self-service analytics at scale. Example projects:* Leveraged dbt-core to enable multi-tenant dbt runs.* Built robust observability to track model performance and usage.* Enabled multi-warehouse functionality to optimize Snowflake cost.* Design frontend events modeling architecture with user sessionization built-in.

Design Single Source of Truth workflows for analytics and business units. Example projects include:* Worked with engineering teams and business units to design and build "core" datasets in Redshift that serve as SSOT for analytics and reporting.* Introduced and drove Looker adoption for internal and external reporting use cases.* Migrated dbt and looker objects from Redshift to Snowflake during company-wide data warehouse migration.

Build scalable data pipelines that consolidate external data sources, derive advanced analytics, and power data science models. Member of data engineering team responsible for designing, developing, and maintaining Betabrand's data model. Meet with external stakeholders to plan and prioritize data projects. Implement Betabrand's Looker instance and empower business users to become more data-driven.Tech: Python | Airflow | Google Cloud Platform (Cloud Composer, Cloud Storage, BigQuery)

Setup and reported on various email A/B tests. Performed ad-hoc requests to help provide insights to external stakeholders. Built predictive models from scratch including RFM model to predict Customer Lifetime value. Identified and measured key KPI's to assist the e-commerce team in budget optimization. Built 100's of SQL backed dashboards for real-time reporting and insights. Optimized email campaigns through various personalization techniques including personalized send time, product recommendations, and data backed drip campaigns for re-purchase.Tech: Redshift | MySQL | Python | Periscope

Capstone Project: Machine Scouting - A Customer Segmentation Approach to NFL QuarterbacksTeams spend enormous resources, both time and money, evaluating players and forecasting a quality of fitness for their team. What I have noticed over the years as that professional football teams have a really hard time determining which college quarterbacks are going to succeed. I felt the evaluation process was missing out on the habits and tendencies of quarterbacks from play to play instead of game to game.When doing research for my project, I noticed the play-by-play tables were surprisingly rich in detail in regards to the passing plays. So I built a web crawler that scraped all of these tables dating back to 1994, a little over 1 million plays. I then engineered features based on the text in each play description to create my feature matrix. After that, I used unsupervised learning techniques to segment these quarterbacks based on their success and tendencies to throw in certain quadrants of the field. In the end, I was able to find 4 groups that really separated the quarterbacks and was able to identify traits that professional scouts spend hours trying to identify.

+ Worked directly alongside the COO with planning and developing operations for a branch office.+ Hired and trained staff to develop local operations in Accounting, Marketing, and Localization.+ Oversee all operations at the branch office and report directly to COO & CEO.

+ Co-founded and developed the business development team that helped expand operations internationally. + Negotiated terms and contracts with payment providers that directly increased profits.+ Analyze data from users and games to help Product Managers improve their quality and success.+ Oversee and organize the ground work and research for entry into all new markets

+ Content editor for a newly developed content management system (CMS) for new website launch.+ Assisted the digital team with a new website launch for all magazine markets.