Staff Analyst, Analytics - Jumbo Insights

Location: Hybrid 3 days (offices in NYC, Denver, CO and Charlotte, NC area)

Position Summary: 

We are seeking a highly analytical, client-facing Staff Analyst to support and grow our Analytics team. This role requires strong PBM industry knowledge, advanced data analysis skills, and the ability to translate complex pharmacy benefit, claims, and performance data into clear, actionable insights for clients and internal stakeholders. The ideal candidate will bring a consultative mindset and be comfortable leading in-depth analyses, developing thoughtful recommendations, and presenting findings directly to clients in a polished and confident manner. They will have experience managing business-critical requests, partnering across cross-functional teams, and contributing to a scalable analytics foundation that supports client decision-making and drives measurable value. With 4–6 years of experience in data analytics, this individual will play a key role in promoting efficiency, consistency, and innovation across our Analytics team. 

Key Responsibilities:  

• Lead Client-Facing PBM Analytics 
  • Perform complex analyses across pharmacy benefit, claims, utilization, trend, savings, and performance data to answer client and business questions.
  • Apply strong PBM industry knowledge to interpret results, identify key drivers, and connect findings to client-specific priorities and decision-making needs.
  • Develop client-ready analyses, dashboards, and presentations that clearly communicate insights, recommendations, and potential business impacts.
• Present Insights and Consult with Clients 
• • Present detailed analytical findings directly to clients and internal stakeholders in a clear, polished, and confident manner.
  • Translate complex data, methodology, assumptions, and limitations into business-friendly narratives for technical, operational, and executive audiences.
  • Serve as a consultative analytics partner by proactively identifying opportunities, risks, follow-up questions, and recommended next steps. 
• Execute High-Quality Analytics 
  • Use SQL, Tableau, or other business intelligence platforms, and cloud-based data environments to conduct advanced analysis and reporting.
  • Ensure analyses are accurate, well-documented, reproducible, and supported by appropriate quality checks and sound analytical methodology.
  • Identify opportunities to improve efficiency through automation, reusable frameworks, standardized reporting logic, and improved data practices. 
• Partner Across Teams and Manage Priorities 
  • Partner with product managers, business leaders, client-facing teams, and clients to understand analytics needs, clarify scope, and prioritize requests based on business value and urgency.
  • Manage multiple business-critical analytics requests in a fast-paced environment while communicating timelines, dependencies, risks, and tradeoffs.
  • Collaborate cross-functionally to align analytical work with broader business goals and support consistent, data-driven decision-making. 
• Support Scalable Standards and Compliance 
  • Contribute to analytics standards, documentation, quality controls, and repeatable processes that improve consistency and scalability across the Analytics team.
  • Support knowledge sharing, peer collaboration, and continuous improvement to strengthen team practices and analytical delivery.
  • Ensure adherence to company compliance standards, including the Capital Rx Code of Conduct and reporting of noncompliance.
• Provide Informal Technical and Analytical Leadership 
  • Establish reusable analytical patterns, templates, and documentation that improve consistency, scalability, and quality across the team.
  • Mentor peers through analytical reviews, technical problem-solving, and knowledge-sharing practices.
  • Help raise the bar for analytical rigor by reviewing methodology, assumptions, logic, and interpretation before stakeholder delivery.
  • Encourage experimentation with new tools, techniques, and approaches that improve analytics quality, efficiency, or stakeholder value. 

Qualifications & Experience:  

• 4–6 years of experience in data analytics, business intelligence, healthcare analytics, or a related field.
• Strong PBM industry knowledge, including experience working with pharmacy benefit concepts, claims data, utilization trends, formulary or benefit design considerations, savings analysis, and client reporting metrics.
• Experience analyzing pharmacy claims data and translating claim-level findings into client-ready insights, recommendations, and business implications.
• Proficiency in SQL and business intelligence tools such as Tableau, with the ability to work in cloud-based data environments and maintain strong coding hygiene, documentation, and quality-control practices.
• Ability to perform complex analyses, explain methodology and assumptions, identify key drivers, and synthesize findings into clear business insights.
• Demonstrated ability to present detailed analytical findings to clients and internal stakeholders in a polished, confident, and consultative manner.
• Track record of partnering closely with internal and external stakeholders to scope requests, prioritize work, provide consultative analytics support, and proactively advise on business opportunities or risks.
• Working knowledge of data engineering fundamentals and experience working with cloud-based data warehouses such as Snowflake, BigQuery, or Redshift.
• Proven ability to prioritize and manage multiple business-critical analytics projects in a fast-paced environment while communicating timelines, dependencies, risks, and tradeoffs. 

Preferred Qualifications:  

• Experience working in large-scale, high-growth organizations.
• Knowledge of machine learning or advanced statistical modeling techniques.
• Familiarity with Agile project management methodologies.
• Master’s degree in Computer Science, Actuarial Science, Statistics, Economics, or a related field.
• GitHub and dbt experience. 

Why Join Us?  

• Lead a highly skilled, technical analytics team in a dynamic and data-driven organization.
• Drive strategic decision-making and build a scalable data foundation for business growth.
• Work with cutting-edge technologies and make a meaningful impact on the organization.