
Tom Waterman
Data Build Tool (dbt) Developer
Tom is an experienced data modeler with a decade of experience in the technology sector. He's worked across the data stack in various roles, including data scientist, analytics engineer, and data engineer. His professional experience includes data roles at Facebook and Miro, where he led data warehousing, data modeling, and data platform initiatives.
Portfolio
Experience
Python - 5 yearsSQL - 5 yearsGit - 5 yearsData Science - 5 yearsDocker - 3 yearsRedshift - 3 yearsApache Airflow - 3 yearsData Build Tool (dbt) - 2 yearsAvailability
Preferred Environment
Docker, SQL, Apache Airflow, Python, Data Build Tool (dbt), Snowflake
The most amazing...
...project I've led was a greenfield dbt and Snowflake migration for a hyper-growth SaaS company, which quickly became the foundation of data for the business.
Work Experience
Data Scientist
- Built and managed data infrastructure for a program's in-house CRM platform. Data infrastructure was used for sourcing new leads, monitoring program efficiency, and integrating data sources.
- Managed analytics for a new, experimental product developed for small businesses, including targeting criteria, feature-flags used during release, and developing insights about product adoption.
- Built and maintained lead-scoring models for an on-platform campaign that drove a 30% improvement in cost per campaign objective.
Data Engineer, Product Analyst
Poll Everywhere
- Implemented Airflow and constructed the first data pipelines for the company.
- Managed the building and design of a data warehouse, including integrating data sources.
- Built a lead scoring system that automatically funneled leads to the sales team. The system included data enrichment, scoring, and result tracking.
Business Analyst
Cartesian Consulting
- Built data pipelines and a scoring system to measure and track the prevalence of account sharing for a video streaming service.
- Created revenue and operations tracking dashboards for a sales channel of a US wireless carrier.
- Developed cost-allocation models to assess the profitability of individual enterprise customers for a US communications service provider.
Experience
Greenfield Airflow Deployment
The app was also responsible for calculating the company's KPIs including daily active users, performing lead-scoring of new users, and monitoring the quality of data ingestion. The data pipelines in the application were used for several mission-critical projects, including A/B testing new pricing models and validating the effects of new feature releases of the company's customer-facing applications.
Lead Scoring and Recommendation System
A/B Testing for Pricing Changes and New Feature Releases
Skills
Languages
Python, SQL, R, Snowflake
Frameworks
Flask, Presto DB
Libraries/APIs
Pandas, NumPy, Flask-RESTful
Tools
Amazon Athena, Apache Airflow, Docker Compose, Jupyter, Git
Paradigms
Data Science, Database Design
Storage
PostgreSQL, Redshift, MySQL, Database Architecture, MongoDB
Other
Data Engineering, Analytics, Dashboard Design, Data Scraping, Data Mining, Modeling, Data Build Tool (dbt)
Platforms
Amazon Web Services (AWS), Docker, Ubuntu
Education
Bachelor's Degree in Mathematics and Statistics
Boston University - Boston, Massachusetts