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Part‑time (≈20 hrs/week) • 3‑month project • Remote (US‑friendly hours)
Why This Role Matters
Legion Health’s data lives in half‑automated dashboards, ops spreadsheets, and ad‑platform exports. We need someone to wire everything together, instrument every click and server outcome, and make growth metrics self‑serve for the entire team.
What You’ll Deliver
1 – Centralized Growth Metrics & Dashboards (Required)
* Pipe data from GA4, ops scorecards, billing, EMR, and provider‑availability feeds into one source of truth in PostHog/Segment.
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Centralize and automate the collection of the KPIs that matter for our insurance‑based healthcare service:* Paid and organic CAC, plus CAC per retained patient
* Step‑by‑step onboarding conversion (landing page start → eligibility complete → benefits verified → intake finished → first appointment booked and shown)
* Real‑time provider availability and idle time
* Time‑to‑intake and time‑to‑first visit
* Patient retention, weekly LTV, churn, and net margin per visit
* Claim‑denial rates and gross‑to‑net reimbursement
* etc.
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Automate dashboards, Slack/email digests, and threshold alerts (e.g., CAC spikes, idle‑provider alerts) for real‑time decision‑making.
* Keep all
metric definitions in a living data dictionary so finance, growth, and clinical ops speak the same language.
2 – End‑to‑End Analytics Stack (Future, if Successful in #1)
* Fully implement PostHog, Segment, and Google Analytics 4 for complete funnel and behavioral insights.
* Instrument
every product event with both client‑side “click” and server‑side “success” calls; build a structured
tracking plan that documents event names, purpose, properties, and collection points.
* Deploy
Segment for clean, schema‑driven event collection and bi‑directional integrations with ads, email, and data warehouse.
* Validate that our event‑driven architecture flows seamlessly from first click to patient conversion and downstream ops automations.
3 – Democratized Data Access (Future, if Successful in #1)
* Stand up BigQuery (or Snowflake) as the warehouse of record; schedule Segment/PostHog exports.
* Layer a BI tool such as
Mode or Metabase for ad‑hoc SQL analysis.
* Build a shared library of saved queries and dashboards for recurring metrics (e.g., funnel drop‑off by payer, LTV by lead source).
* Run hands‑on workshops so ops, product, and marketing teammates can adapt basic SQL and pull their own insights without waiting on you.
4 – Reporting & Knowledge Transfer (Required)
* Replace manual daily roll‑ups with self‑updating views accessible company‑wide.
* Deliver concise weekly memos summarizing data quality, new instrumentation, and experiment read‑outs.
* Document the full event taxonomy, data model, and dashboard logic; hand off maintenance playbooks to future data or growth hires.
You’ll Be Successful If You…
* Automate and centralize all spreadsheet KPIs and standalone tool metrics into PostHog dashboards that the team actually uses.
Must‑Have Skills
* Analytics ingestion & modeling: Hands-on experience piping data from GA4, ops scorecards, billing systems, EMR exports, and provider-availability feeds into a modern analytics platform (e.g., PostHog, Mixpanel, Amplitude, etc.) as a single source of truth.
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KPI centralization & automation: Proven ability to define, calculate, and automate key insurance-based metrics (CAC, onboard-to-visit funnels, provider availability, time-to-intake/visit, retention, LTV, churn, denial rates, net margin, etc.).
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Dashboard & alerting: Skilled at building self-updating PostHog dashboards, Slack/email digests, and threshold alerts (e.g., CAC spikes, idle-provider warnings) for real-time decision-making.
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Data dictionary governance: Experience creating and maintaining a living data dictionary so finance, growth, and clinical ops teams share one consistent vocabulary.
Nice‑to‑Have Skills
* Alternate event pipelines: Experience with Segment, RudderStack, or similar for schema-driven event collection
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Warehouse & BI tools: Hands-on with BigQuery or Snowflake setup/maintenance and BI platforms (Mode, Metabase, Looker) for ad-hoc analysis.
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Advanced SQL analytics: Comfort writing complex joins, window functions, and cohort/LTV analyses across product, revenue, and ops tables.
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JS/TS tagging & schema design: Fluency in JavaScript/TypeScript client- and server-side event instrumentation and data schema modeling.
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Data-ops communication: Proven ability to teach non-technical teammates to self-serve metrics—clear documentation, workshops, and playbooks.
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HIPAA-adjacent analytics: Familiarity with telehealth or healthcare-compliant data stacks and workflows.
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Experimentation & attribution: Knowledge of attribution modeling, A/B testing frameworks, or PostHog Experiments API.
Engagement Details
* Time: ~20 hrs/week for X months.
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Compensation: Competitive hourly or project rate.
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Resources: Budget for any tooling you recommend; direct access to engineering, growth, and ops leads.
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about 24 hours ago
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