Senior Data Analyst - Clinican Experience

Hybrid, Palo Alto OR San Francisco (Hybrid - 2 days/week in office)

Reports to: Director Data Science + Analytics

About the Role

We are looking for a highly analytical and business-minded Senior Data Analyst to design, build, and own the end-to-end analytical framework for our most critical operational asset: our clinician workforce. In this role, you will own the data ecosystem spanning the entire clinician lifecycle-from the moment a provider enters our recruiting funnel, through onboarding, credentialing, and state licensing, to their ongoing clinical performance, operational efficiency, and downstream business impact on patient retention.

You will develop performance frameworks that merge operational SLAs (e.g., on-time arrival, inbox turnaround times) with clinical quality and safety metrics. Additionally, you will lead our efforts in provider interaction analytics, creating evaluation and scoring logic to quantify qualitative behavioral dimensions, such as clinician empathy from consultation transcripts. Sitting at the intersection of Clinical Operations, Quality, Talent, Business Strategy, and Product, you will serve as the primary analytical partner to our Clinical Leadership and Executive team.

What You’ll Do

1. Clinician Lifecycle & Funnel Analytics

• Recruiting & Onboarding Optimization: Track and analyze the provider hiring funnel to uncover drop-off points, streamline time-to-hire, and improve conversion rates across clinical specialties.
• Credentialing & Licensing Efficiency: Build predictive frameworks and monitoring dashboards to reduce state-by-state licensing bottlenecks and decrease provider time-to-first-consultation.
• Cohort Retention & Attrition Modeling: Analyze first-year clinician retention trends, identifying early-warning indicators of burnout or regrettable turnover, and evaluating the long-term impact on operational capacity.

1. Operational Performance & Efficiency Metrics

• Operational SLA Tracking: Design and maintain performance scorecards tracking operational efficiency metrics, including appointment on-time start rates, EMR/EHR inbox turnaround times, chart completion speed, and panel utilization.

1. Clinical Quality, Safety & Interaction Scoring

• Transcript & Empathy Analytics: Establish scoring frameworks and evaluation logic to extract insights from visit transcripts. Quantify qualitative provider attributes (e.g., patient rapport, empathy, active listening) using sentiment and text analytics LLM tools.
• Clinical Safety & Quality Alignment: Partner with the Clinical Quality and Safety teams to incorporate chart audit scores and clinical safety compliance into unified provider scorecards.

1. Downstream Patient & Business Impact

• Clinician Impact on Patient Retention: Conduct causal and correlation analyses linking specific clinician behaviors, operational SLAs, and empathy scores directly to patient retention, net promoter scores (NPS), and long-term treatment plan adherence.
• Executive Reporting & Strategic Guidance: Translate complex provider performance data into clear executive dashboards and strategic frameworks that directly inform clinician compensation, training programs, and operational workflows.

Data Analysis, Data Science, Data Analysis, Ecosystems, Onboarding, Analysis Skills, Licensing, Time Management, Business Strategy, Service Level Agreement (SLA), * Advanced SQL & Data Modeling: Expert-level SQL skills for querying, transforming, and modeling complex relational databases across disparate operational and EHR systems.

• Python Proficiency: Advanced skills in Python for statistical analysis, cohort modeling, survival analysis, and text/sentiment processing.
• Data Visualization & BI: Proven ability to design intuitive, executive-ready dashboards in modern BI tools (e.g., Looker, Tableau, PowerBI).
• Text Analytics & NLP Awareness: Familiarity with text mining, sentiment analysis, or prompt-based LLM evaluation frameworks for processing qualitative data (transcripts, chat logs, survey notes).
• Modern Analytics Stack & AI Tools: Experience with cloud data warehouses (Snowflake, BigQuery, Databricks) and active adoption of modern AI tools (e.g., LLMs for coding efficiency, automated insights) to accelerate analytics workflows.

Analytical & Domain Capabilities

• Healthcare Operations Intuition: Understanding of clinical operations, provider scheduling, EMR/EHR workflows (e.g., Epic, Athena, or proprietary telehealth EHRs), and clinical quality metrics.
• Behavioral & Lifecycle Analytics: Experience with cohort analysis, retention modeling, and constructing behavioral/qualitative scoring models.
• Strategic Problem Structuring: Ability to take unstructured business and clinical questions and translate them into rigorous, answerable quantitative frameworks.
• Cross-Functional Influence: Demonstrated ability to partner effectively with non-technical stakeholders, particularly Clinical Lead/Medical Directors, Operations leads, and Talent teams.

Experience

• 5+ years of data analytics experience delivering high-impact operational or workforce insights.
• Healthcare Experience: Strong preference for background in Digital Health, Telehealth, Tech-enabled Medical Groups, or Health Operations. (Strong candidates with backgrounds in People Analytics/People Data Science with exposure to operational telemetry are also encouraged to apply.)
• Bachelor’s or Master’s degree in Quantitative discipline (Data Analytics, Health Informatics, Statistics, Industrial Engineering, Economics) or equivalent practical experience., At this time, Midi is unable to provide visa sponsorship. Candidates must be authorized to work in the U.S. without current or future sponsorship needs., At this time, Midi is unable to provide visa sponsorship. All Candidates must be authorized to work in the United States without current or future sponsorship needs.

The base salary range is 150-175K and will depend on experience. Midi pays a competitive base salary, plus equity and benefits.

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