Data Analyst

This is a fully remote position, open to applicants in Philippines.

📋 Description

• Develop, manage, and continuously enhance executive and operational dashboards utilizing various data sources such as BigQuery, Google Analytics, Odoo, Abacus AI, and others.

• Create a centralized metrics layer that consolidates data from marketing, sales, customer success, and physician experience into a unified, coherent source of truth.

• Ensure that all critical business metrics — including churn rate, LTV, conversion rates, cohort performance, revenue per client, and physician supply/demand by state — are monitored in a single, easily accessible, and well-maintained location.

• Provide regular reporting to leadership featuring clear visualizations, trend analysis, and suggested actions.

• Establish automated alerts and monitoring systems to notify leadership when key metrics deviate from expected ranges, thereby reducing the need for manual reviews.

• Utilize Abacus AI and other AI-driven tools to expedite analysis, reveal patterns, and develop predictive models that would otherwise demand significant manual effort.

• Examine churn and retention trends across client cohorts to pinpoint when clients are most vulnerable and what behavioral or operational factors may lead to cancellations.

• Construct and maintain survival cohort models to gain insights into client lifetime value and identify critical inflection points where clients may stabilize or disengage.

• Highlight early warning signs in client behavior — such as invoice review frequency, support ticket volume, platform inactivity, or communication patterns — to assist Customer Success in taking proactive measures instead of reactive ones.

• Assess the effectiveness of retention strategies, discount programs, and re-engagement initiatives through thorough before-and-after analyses.

• Model the revenue implications of reducing churn by specific percentage points to assist leadership in prioritizing retention investments.

• Analyze conversion pathways across the client platform and website — from page views to registrations, intro calls booked, and active subscriptions — to identify where qualified prospects drop off.

• Dissect conversion performance based on physician listing attributes, source channel, device type, and registration path to uncover significant optimization opportunities.

• Measure the effects of product modifications — such as blurred listing features, rate changes, profile enhancements, or UI updates — on registration and conversion rates.

• Support Marketing with analytics from Google Analytics and BigQuery to evaluate traffic quality, campaign effectiveness, and differentiate between qualified and unqualified demand.

• As new behavioral tracking tools (e.g., PostHog or similar session-level analytics) are implemented, take responsibility for analyzing individual engagement data and correlating it with downstream outcomes.

• Create and uphold structured client and physician persona profiles grounded in actual platform data — encompassing demographics, specialty, state, practice type, rate sensitivity, and behavioral patterns.

• Analyze physician supply and demand by state, specialty, and availability to assist the Physician Experience team in identifying recruitment focus areas for optimal business impact.

• Investigate the traits of successful versus unsuccessful collaboration relationships and translate findings into actionable advice for Customer Success, Sales, and the matching process.

• Collaborate with the Operations Team — responsible for Customer Service Representatives handling inbound calls, subscription management, and billing — to identify data requirements and create analytical support tailored to their workflows.

• Analyze inbound call volumes, inquiry types, and resolution patterns to highlight trends that can enhance operational efficiency and service quality.

• Monitor and report on subscription activity — new activations, cancellations, and payment failures — providing the Operations Team with timely insights into the health of the subscriber base.

• Develop analytics for billing and collections to track invoice aging, dispute frequency, and payment behavior, enabling the team to proactively manage accounts before issues escalate.

• Identify recurring operational bottlenecks — such as high-volume inquiry categories or common billing friction points — and convert findings into process improvement recommendations.

• Assist the Operations Team in establishing KPIs and reporting schedules to ensure consistent and objective tracking of Customer Service performance.

• Partner with department heads to establish reliable baseline metrics that ground quarterly OKR-setting in actual data rather than estimates.

• Create and maintain a shared KPI scorecard for leadership meetings, ensuring all metrics are consistently defined, sourced from the same data, and comparable over time.

• Identify and resolve discrepancies in how different teams calculate the same metrics (e.g., differing churn rate definitions) and drive alignment towards a single authoritative methodology.

• Construct the reporting infrastructure that allows leadership to monitor OKR progress in real time instead of waiting for end-of-quarter reviews.

• Collaborate with the CEO and technical team to enhance the underlying data infrastructure — ensuring data from the platform, CRM, billing system, website, and marketing tools flows into a reliable, queryable layer.

• Document data definitions, metric methodologies, and dashboard logic to ensure that analytical work is transparent, reproducible, and not reliant on any single individual.

• Assess and recommend new data tools and integrations as the company scales, balancing capability with cost and complexity.

• As the client grows, help define what a more advanced data function could resemble — potentially including additional analysts, data engineers, or specialized roles.

• Respond to leadership requests for one-off analyses as business questions arise — ranging from pricing strategies to geographic expansions to investment preparations.

• Provide analytical support to cross-functional initiatives such as product launches, sales team changes, or redesigns of retention programs.

• Investigate new data sources and analytical techniques as they become available, fostering a continuous improvement mindset within the function.

⛳️ Requirements

• A minimum of 3+ years of experience in a data analyst or business intelligence capacity, preferably in a SaaS, marketplace, subscription, or technology environment.

• Proficiency in SQL for querying, transforming, and analyzing data from relational databases and data warehouses.

• Experience in creating dashboards and data visualizations using tools like Google Looker Studio, Tableau, Power BI, or similar platforms.

• Practical experience with Google Analytics and Google BigQuery, or equivalent data warehousing and web analytics solutions.

• Strong analytical skills with the capability to translate complex, ambiguous data into clear, actionable business insights and recommendations.

• Excellent communication skills in English — both written and verbal — with the ability to convey findings to non-technical stakeholders, including senior leadership.

• A self-starter with a strong sense of ownership; comfortable working independently in a dynamic, fast-paced startup setting where data may be incomplete or imperfect.

• Curiosity and business intuition — you don't just respond to the questions posed, you seek to understand what questions should be asked.

• Familiarity with cohort analysis, LTV modeling, churn/retention analysis, or other subscription-related analytics.

• Knowledge of Abacus AI or similar AI-powered analytics and business intelligence platforms.

• Exposure to product analytics or behavioral tracking tools such as PostHog, Mixpanel, or Amplitude.

• Familiarity with CRM or ERP platforms; experience with Odoo, Salesforce, HubSpot, or similar is advantageous.

• Experience with marketing analytics platforms — Google Ads, Meta Ads, or comparable — is beneficial.

• Understanding of US healthcare concepts (e.g., collaborative practice, NP/PA scope of practice, telehealth) is an asset but not mandatory.

• Comfort with or interest in AI/ML techniques — regression, classification, clustering — and their applications in business analytics challenges.

• Experience in a marketplace, two-sided platform, or healthcare technology company is a plus.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Flexible working hours and remote work options.

• Opportunities for professional development and growth.

• Comprehensive health and wellness benefits.

• A supportive and collaborative work environment.