Director of Data

Overview

The Director of Data & Analytics is the architect and accelerator of Rugiet’s entire data ecosystem — infrastructure, analytics, attribution, forecasting, and personalization. You’ll lead a small, high-impact team while driving the evolution of our stack as we migrate into Snowflake and build a scalable, ML-ready foundation.

You’ll report directly to the CGO and partner closely with Marketing, Product, Engineering, Operations, and Finance. This is a role for someone who can zoom between big-picture strategy and hands-on analytical depth without dropping a beat.

What You’ll Do

Data Strategy, Leadership & Organizational Enablement

• Define Rugiet’s data strategy and lead the team executing it — from infrastructure to analytics to modeling.
• Manage and develop 2 analysts/data engineers, raising the bar on analytical rigor, ownership, and output.
• Create a transparent intake and prioritization system so stakeholders understand what’s happening, why, and when.
• Introduce higher standards for what qualifies as a data request, focusing the team on analysis over mining.
• Champion BI self-service by training teams across the company and building intuitive, reliable dashboards that reduce dependency on analysts.

Infrastructure Ownership: Snowflake, ETL & BI Tooling

• Lead Rugiet’s migration to Snowflake and design a warehouse optimized for speed, quality, and massive growth.
• Optimize ETL pipelines (Segment → Snowflake → BI layer) that enable near-real-time reporting where it matters.
• Shift the company away from one-off dashboards and inconsistent models toward reusable, governed, version-controlled assets.
• Establish data governance standards — schemas, taxonomies, naming conventions — that prevent chaos as we scale.
• Assess long term scalability of current BI tooling and build out more robust self-service offerings for the organization to adopt for key decision making

ML, Personalization & Product Partnership

• Partner with Product and Engineering to develop data inputs, segmentation logic, and feature sets used in personalization and ML-driven experiences.
• Translate behavioral and lifecycle data into algorithm-ready structures that improve retention, engagement, and patient outcomes.
• Ensure data pipelines and infrastructure support scalable training, monitoring, and continuous optimization of ML models.

Growth & Retention Analytics (Attribution, LTV, Forecasting)

• Build LTV models and LTV curves sliced by acquisition channel, offer, audience, and treatment category.
• Create daily multi-touch attribution reporting and cut reliance on costly external tools by bringing core capabilities in-house.
• Build Rugiet’s retention OKRs and dashboards within BI tools — with intuitive views for the whole business.
• Attribute cancellations and churn to specific lifecycle, email, and SMS campaigns with clarity and statistical rigor.
• Architect and analyze A/B tests across the site, funnel, CRM, and product experience — unblocking high-conversion opportunities.
• Develop MMM (Marketing Mix Modeling) in Python to inform budget allocation across nine figures of annual spend.
• Partner with Finance on forecasting models for demand, inventory, and revenue planning.

What You Bring

• 7+ years in Data & Analytics with 2+ years leading teams; strong preference for high-growth DTC or telehealth experience.
• Hands-on mastery of modern data stacks:
• • Warehousing: Snowflake (or equivalent)
  • ETL/Pipelines: Segment, Fivetran, dbt, or similar
  • BI: Domo (strong preference), Looker, Mode
  • Analytics: GA4, Segment, Mixpanel
  • Attribution: Northbeam, MTA structures, familiarity with MMM
• Advanced SQL and strong data-modeling discipline — you build scalable foundations, not just one-off queries.
• Proven ability to turn messy data into clean insights and communicate them clearly to executives.
• Experience enabling BI self-service and building stakeholder capability.
• Strong understanding of data governance and privacy/security practices.

Nice to have

• Python or R experience for LTV modeling, churn prediction, MMM, forecasting, and ML feature engineering.
• Experience with Blotout, Growthbook, or similar tools.
• Background in healthcare, wellness, or subscription businesses.
• Experience building or supporting personalization/ML systems in partnership with Product.