Tom Waterman, DBT Developer in San Francisco, CA, United States
Tom Waterman

DBT Developer in San Francisco, CA, United States

Member since December 10, 2019
Tom is a data scientist from Facebook with more than five years of experience in the technology sector. He's also worked as a data engineer for fast-growing SaaS companies, helping to build and manage their data infrastructure. He started his career as an analyst at a data consulting firm after graduating from Boston University with a degree in mathematics and statistics. Tom is looking forward to working on new challenges that help clients achieve their goals.
Tom is now available for hire

Portfolio

Experience

Location

San Francisco, CA, United States

Availability

Part-time

Preferred Environment

Python, Airflow, Jupyter, Pandas, Flask, SQL, DBT, Redshift, Presto, Postgres, MySQL, Docker, Git

The most amazing...

...application I've ever built was a custom A/B testing framework that enabled the company's developers to split test new features with just two lines of code.

Employment

  • Data Scientist

    2018 - PRESENT
    Facebook
    • 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.
    Technologies: Python, SQL
  • Data Engineer, Product Analyst

    2016 - 2018
    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.
    Technologies: Python, SQL, Airflow
  • Business Analyst

    2014 - 2016
    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.
    Technologies: Python, SQL

Experience

  • Greenfield Airflow Deployment (Development)

    A greenfield Docker-based Airflow deployment used for building out the company's first data pipelines. The Airflow app managed ETL jobs that connected the company's internal services and vendor platforms with their data warehouse.
    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 (Development)

    Built a lead scoring system that automatically ranked all new users based on their propensity to become qualified leads, and then allocated the most qualified leads to the sales team each day for further qualification. The system used signals from data enhancement sites like Clearbit, engagement with marketing content on the company's website, and product usage to help improve the efficiency of our inside sales team and lead nurturing campaigns.

  • A/B Testing for Pricing Changes and New Feature Releases (Development)

    Built data analytics, including data pipelines and statistical significance calculations, for A/B tests of the company's pricing plans and feature releases. Provided recommendations based on that analytics which significantly affected the company's pricing strategy and product roadmap.

Skills

  • Languages

    Python, SQL, R
  • Frameworks

    Flask, Presto DB
  • Libraries/APIs

    Pandas, NumPy, Flask-RESTful
  • Tools

    AWS 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, AWS, DBT
  • Platforms

    Docker, Ubuntu

Education

  • Bachelor's degree in Mathematics and Statistics
    2010 - 2014
    Boston University - Boston, Massachusetts

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