Data Analyst
$90k - $130kFabric Health
About the Role Fabric is looking to bring on a Data Analyst to provide customer insights and support our medical leadership through actionable reporting. As part of our analytics team, you partner with the clinical organization to deliver strategic analyses and build automated reporting around clinical operations and health outcomes. You will dive into complex datasets to analyze trends, identify opportunities, and quantify the potential value of new initiatives. Your work helps ensure our clients have clear visibility into the clinical value Fabric provides, supporting the continuous improvement of our medical practice to best serve our patients. This role requires proven quantitative and critical thinking skills along with a solid understanding of healthcare analytics. As a vital contributor to a lean team, you clearly communicate complex findings to diverse audiences, collaborate across multiple functions, and leverage modern AI tools to accelerate data processing and generate insights. What You'll Do As a Data Analyst, your primary responsibilities include:
- Build and maintaining reporting that tracks physician performance, care quality, and consistency of clinical standards across the platform.
- Design dashboards and visualizations that make clinical and business metrics easy to act on for both clinical and non-clinical leaders.
- Partner closely with our client-facing organization to surface clinical insights for customers and prospects.
- Collaborate with clinical operations and physician enterprise leaders to translate open questions into clear, well-scoped analyses.
- Write and maintaining SQL for the data warehouse to transform raw clinical and operational data into analysis-ready datasets, utilizing AI coding assistants to accelerate query development.
- Collaborate with product and engineering teams to improve the quality, structure, and reliability of underlying clinical data.
- Support ongoing reporting needs to help the team move from one-off requests toward scalable, repeatable reporting.
- Leverage AI tools for advanced data cleaning, initial pattern recognition, and drafting analytical summaries to increase efficiency.
- You enjoy translating ambiguous clinical questions into clear, actionable data models and dashboards.
- You have a solid foundation in healthcare analytics and understand the nuances of clinical and operational data.
- You excel at bridging the gap between technical data engineering and business-facing clinical leadership.
- You are proactive in seeking out ways to scale reporting rather than manually answering the same questions repeatedly.
- You are an early adopter of technology, actively using AI tools to write queries faster and streamline your analytical workflows.
- You prefer working with perfectly clean, strictly structured data over navigating the messy reality of real-world healthcare datasets.
- You want to focus solely on building complex machine learning models rather than delivering practical, descriptive analytics and BI reporting.
- You struggle to communicate technical findings to non-technical stakeholders in a clear, digestible manner.
- You prefer traditional manual coding workflows and are hesitant to adopt AI assistants to scale your data analysis tasks.
- 2+ years of experience analyzing data in a professional setting, ideally within healthcare.
- Proven proficiency in SQL.
- Experience building dashboards or reports in a BI tool such as Tableau or Thoughtspot.
- Familiarity with Python or R for complex analyses.
- Proficiency in utilizing modern AI assistants for query generation, data cleaning, and workflow automation.
- Bachelor's degree, preferably in a quantitative discipline; an advanced degree is a plus.
- Comfort managing multiple analysis projects at once and adapting to shifting priorities in a fast-paced environment.
- Familiarity with common healthcare datasets, standards, and measures such as HEDIS.
- Experience with analytics tools such as Heap, Mixpanel, or Amplitude.
- Experience with A/B testing, including statistical hypothesis testing methodologies.
- Experience working within Databricks.
- Verify the Domain: Official recruitment emails will only come from addresses ending in @fabrichealth.com or @gem.com. No other domain names are legitimate.
- Official Interview Tools: We use Gem for our recruitment process and Google Meet for all video interviews. Google Meet is always the platform used for your first interview; you will never be sent a Zoom link to set up or conduct an initial interview. All interviews are conducted via video unless specifically stated by our team as an audio call. We never conduct interviews via chat, social media, Skype, or WhatsApp.
- Zoom Usage: Zoom is utilized only for specific meetings set directly by our team for purposes outside of the standard interview process (e.g., coordination or onboarding discussions). It is never the first link you will receive from us.
- Authorized Contact & Texting: Fabric will only contact you if you have submitted an application or if you are connected to a current employee who shared your information with us. We will only send text messages if you have provided explicit authorization and consent, either through your application or while communicating directly with our team. If you have not explicitly authorized us to reach out, treat any SMS or unsolicited outreach as fraudulent and do not respond.
- Sensitive Data: We will never ask you for sensitive personal or financial documents (ID, banking info, SSN) during the application, interview, or candidacy stages. All sensitive data is handled through secure internal systems post-offer.
- Verify the Team: You can reference LinkedIn to verify members of our recruiting team; however, please remain vigilant as scammers may create fraudulent profiles. Always cross-reference the sender's email domain with our official @fabrichealth.com address.
Vacancy posted 5 days ago
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