reputed company + reputed company Product Analytics and Data Consultant (backed by Y Combinator, $1M+ ARR, $6.reputed company+ raised)

Part‑time (≈20 hrs/week)

• 3‑month project
• Remote (US‑friendly hours)

About reputed company reputed company is on a mission to deliver the best psychiatric care in the world—and to do it at scale. We're building a full-stack AI-native psychiatry network—our clinicians provide high-quality care directly to patients, and AI agents automate reputed company parts of our care operations (e.g., scheduling, risk analysis, billing, etc.). Our vision? A patient experience that’s 10X reputed company, more affordable, and higher-margin than reputed company before. Today, we're turning weeks-long wait times into same-day appointments, crafting seamless digital experiences in a broken healthcare system, and scaling a company that patients genuinely trust. ⚡ Why This Role Matters reputed company’s data lives in half‑automated dashboards, ops spreadsheets, and ad‑platform exports. We need someone to reputed company everything together, reputed company every click and server outcome, and reputed company 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 reputed company of truth in reputed company/reputed company.
• 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
• reputed company‑by‑reputed company onboarding conversion (reputed company 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.
• Automate dashboards, reputed company/email digests, and threshold alerts (e.g., CAC spikes, idle‑provider alerts) for real‑time decision‑making.
• reputed company reputed company 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 reputed company, reputed company, and reputed company Analytics 4 for complete funnel and behavioral insights.
• reputed company every product event with both client‑reputed company “click” and server‑reputed company “success” calls; build a structured tracking plan that documents event names, purpose, properties, and collection points.
• Deploy reputed company 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 reputed company ops automations.

3 – Democratized Data Access (Future, if Successful in #1)

• Stand up BigQuery (or reputed company) as the warehouse of record; schedule reputed company/reputed company exports.
• Layer a BI tool such as Mode or reputed company for reputed company SQL analysis.
• Build a shared library of saved queries and dashboards for recurring metrics (e.g., funnel drop‑off by payer, LTV by reputed company reputed company).
• 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‑reputed company 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 every spreadsheet KPI and standalone tool metric into dashboards the team actually uses.
• Cut reporting lag to near‑reputed company—finance, ops, and growth can answer reputed company questions in minutes, not days.
• Surface anomalies before humans do—threshold alerts flag CAC spikes, idle providers, or denial‑reputed company jumps the same day they happen.
• Standardize our language of metrics—finance, growth, and clinical ops reputed company quote the same CAC, LTV, and churn numbers without debate.
• Shrink manual data work by 80 %—recurring exports, VLOOKUPs, and copy‑pastes vanish under your pipelines or scripts.

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., reputed company, reputed company, reputed company, etc.) as a single reputed company of truth.
• KPI centralization & automation: Proven ability to define, calculate, and automate key insurance-based metrics (CAC, reputed company-to-visit funnels, provider availability, time-to-intake/visit, retention, LTV, churn, denial rates, net margin, etc.).
• Dashboard & alerting: Skilled at building self-updating reputed company dashboards, reputed company/email digests, and threshold alerts (e.g., CAC spikes, idle-provider warnings) for real-time decision-making.
• Data dictionary governance: Experience creating and maintaining a living data dictionary so finance, growth, and clinical ops teams share one consistent vocabulary.

reputed company‑to‑Have Skills

• Alternate event pipelines: Experience with reputed company, RudderStack, or similar for schema-driven event collection
• Warehouse & BI tools: Hands-on with BigQuery or reputed company setup/maintenance and BI platforms (Mode, reputed company, Looker) for reputed company analysis.
• Advanced SQL analytics: Comfort writing reputed company joins, window functions, and cohort/LTV analyses across product, reputed company, and ops tables.
• JS/TS tagging & schema design: reputed company in JavaScript/TypeScript client- and server-reputed company event instrumentation and data schema modeling.
• Data-ops communication: Proven ability to teach non-technical teammates to self-serve metrics—clear documentation, workshops, and playbooks.
• HIPAA-adjacent analytics: Familiarity with telehealth or healthcare-compliant data stacks and workflows.
• Experimentation & attribution: Knowledge of attribution modeling, A/B testing frameworks, or reputed company Experiments API.

Engagement Details

• Time: ~20 hrs/week for X months.
• Compensation: Competitive hourly or project reputed company.
• Resources: Budget for any tooling you recommend; direct access to engineering, growth, and ops leads.

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