Benjamin Engen

Promoted after my first full year to become The Zebra's first staff level Analytics Engineer and the Data Team’s chief technical liaison to the rest of the company. In this role I led all subsequent initiatives impacting more than one team.

• Kicked-off and oversaw a year-long, master data management initiative to unify user data under a single profile, creating a 10% improvement in user acquisition attribution.
• Redesigned the data warehouse architecture within 18 months, transitioning from ad-hoc models to standardized data products oriented around clearly defined business entities.
• Created and maintained a process for optimizing and cutting Snowflake compute that led to a 30% reduction in Snowflake credit consumption within six months of deployment.
• Began the implementation of a strategy to improve the monitoring of personally identifiable information (PII) by utilizing dbt to track the lineage of such information through our data warehouse.
• Developed a data product strategy and analytics roadmap for the adoption of a suite of business-facing Looker Explores and visualizations built around the Metric Tree framework.
• Completely overhauled the business' approach to marketing attribution, creating a new data pipeline and Looker Explore enabling side-by-side comparison of common methods of marketing attribution.
• Created and led an informal training program for my fellow Analytics Engineers called the Analytics Engineering Guild that somehow grew into one of the most attended and impactful standing meetings in the Engineering Department.
• First engineer within the Data Department to receive a unanimously "exceptional" rating in every category of my annual performance review.

Owned and maintained the dbt repository that managed the data assets necessary to power business intelligence for The Zebra.

• In my first six months, led the data implementation during the transition of our entire sales CRM with zero gaps in our reporting and no sustained downtime.
• Led a two-month, cross-functional effort collaborating with our finance stakeholders to audit our financial data and eliminate reporting errors in advance of our annual audit.
• Developed the first coherent framework for the better governance of our data via stronger monitoring, testing, alerting, and organization.
• Introduced monitoring for native dbt tests via Monte Carlo.
• Created standards for the creation of data monitors "as code" within our dbt repository.
• Audited all existing alert configuration to ensure the right people received the right alerts.
• Added support for monitoring the performance and build times of our dbt data models within Monte Carlo.
• Restructured asset tagging and descriptions to make tables and columns more easily discoverable and to clarify their appropriate use.

Led the design and deployment of the data infrastructure from scratch, taking the organization from a collection of poorly maintained Google sheets to a centralized data warehouse, metrics layer, and Tableau dashboarding in less than a year.

• Led the technical execution of implementing scalable solutions consisting of Fivetran, custom Python, dbt, Tableau, and other tooling to turn raw data into key metric reporting.
• Designed, developed, and deployed a random forest model for lead scoring new contacts.
• Built and maintained seasonally accurate sales and revenue forecasting models.
• Managed projects to implement industry standards and best practices for data modeling, access, documentation, and ensured compliance with security and GDPR regulations.

Developed and maintained econometric models that forecast results for 30 major U.S. economic indicators. For each, I author a persuasive, easy-to-understand, narrative communicating my forecast that is distributed to the company's clientele of institutional investors.

• One of Bloomberg's top 10 most accurate economic forecasters for every major U.S. monthly economic release.
• Frequently cited by major media outlets like NBC and CNN.
• Engineered a direct data link to the BLS for economic data rather than relying on web releases like the rest of the market. Thus allowing our clients to beat the market by minutes when the BLS website went down around a major economic release.

Constellation was a data consultancy that helped clients create useable data and then turn that data into actionable insights, especially in the fields of product and marketing. Over the course of a decade, my team and I helped over 150 clients turn their insights into more effective marketing campaigns and more efficient business operations.

• Provided expert witness testimony in a number of trials, including one currently bound for the U.S. Supreme Court.
• Collaborated on a first of its kind quantitative study on the impact of direct mail marketing accepted for publication in Political Research Quarterly.
• Extensive use of both frequentist and Bayesian A/B testing to improve digital advertising performance.
• Created a machine learning model to improve digital marketing for Girl Scouts and grow cookie sales 10% within the first week of deployment.
• Developed a natural language processing (NLP) sentiment analysis dashboard using Python and SQL to capture and quantify all client earned media.
• Pioneered the use of ARIMA timeseries analysis for budget forecasting and management.
• Managed and mentored junior Data Scientists who have gone on to Harvard, McKinsey, Deloitte, the U.S. State Department, British Parliament, and more.
• Developed and deployed a custom SalesForce environment to manage marketing communications to 3 mln potential customers for Doug for Colorado.
• Developed and deployed a Marketo email marketing campaign that organically grew 50% in 12 months for Doug for Colorado.
• Conducted market research that predicted election margins within one point for Montana Freedom Fund.