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Data

Introduction and Overview

Welcome to Data at Pair Team!

For a comprehensive overview of our team's mission, objectives, scope, and operating model, see the full Data Team Charter.

Mission and Vision

Our mission is to deliver timely, accurate data and insights that enable every team at Pair Team to improve care quality for vulnerable patients, improve efficiency of the care team, and drive strategic growth.

We envision a data-driven Pair Team where every decision—from daily operations to strategic initiatives—is powered by insights, not intuition.

Key Objectives

  1. Build a Data Culture – Ensure all key initiatives are backed by data and insights in order to drive outcomes
  2. Be a Strategic Partner – Earn our seat at the table by partnering with stakeholders to identify the right problems and drive strategy, not just execute requests
  3. Enable Self-Service – Accelerate decision-making by empowering every team to access and understand data independently through intuitive tools, training, and documentation
  4. Build Unshakeable Trust – Become the trusted source of truth through data protection & governance, reliability & quality, and education & transparency

Scope

The Data Team reports into Product and serves as the center for enterprise analytics, data science, data infrastructure, and governance. We are responsible for:

  • Enterprise data strategy
  • Building trusted data models in DBT
  • Enabling self-service capabilities through Looker's semantic layer
  • Maintaining the Snowflake warehouse
  • Ensuring data quality
  • Advanced analytics including machine learning, causal inference, and research publications

We partner closely with the BizOps team (which reports into Operations) to balance enterprise-scale infrastructure with agile, department-specific analysis.

Team

NameRoleEmail
Luke MuellerManager, Analytics Platformluke@pairteam.com
Noah FordSenior Data Scientistnoah.ford@pairteam.com

Resources

High Level Resources

Git Repos

  • analytics-etl: our DBT repo, where data sources are brought together and transformed into the dbt_prod database that Looker Golden Explores read from
  • looker: the semantic layer / BI tool for Pair Team
  • data-science: lightweight repo for various data science projects

Slack Channels

  • #data-alerts: automated alerts for failures in the DBT pipeline or other data issues
  • #pod-data: our team channel, where we post feature releases and host public discussions
  • #support-biz-ops: where we collaborate with BizOps on support tickets across the organization
  • #team-rnd: Product + Engineering + Data shared team channel
  • #data-blog: a place to publicly post analyses out to the whole company

Ticketing

All work is tracked via Asana