Senior Research Scientist - CAHPS/HOS Analytics
Quick Summary
This position is listed on behalf of a partner company, who manages all applications and next steps.
This role applies quantitative research and behavioral science to improve Health Outcomes Survey (HOS) performance and member experiences.
You’ll investigate the factors that influence HOS outcomes and build a stronger evidence base to guide improvement strategies.
The position combines exploratory analysis, survey research, healthcare data, predictive insights, and evidence synthesis.
You’ll work closely with operations and analytics teams to translate complex findings into practical intervention and outreach strategies.
The role requires strong research judgment and the ability to bring structure to ambiguous, high-impact business questions.
You’ll also identify potential leading indicators that can help detect performance risks earlier and inform prioritization.
This is an opportunity to become a trusted analytical thought partner in a collaborative, data-driven healthcare environment.
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Build and continuously strengthen the evidence base around the factors associated with HOS performance and member-reported outcomes.
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Develop and maintain an inventory of potential HOS leading indicators that can support earlier identification of performance risks.
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Monitor behavioral science, survey research, healthcare research, competitive intelligence, and other emerging evidence relevant to HOS improvement.
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Conduct rapid exploratory, ad hoc, and applied analyses using internal and external data sources.
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Translate ambiguous business questions into structured research plans, analytical approaches, and actionable recommendations.
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Independently lead less complex research and analytical projects from problem definition through analysis and recommendations.
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Lead significant components of more complex research initiatives in collaboration with senior leaders and research colleagues.
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Support intervention strategy, prioritization, and portfolio development by translating research findings into practical opportunities.
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Partner with operational teams to guide the appropriate interpretation and application of predictive models for member targeting and outreach.
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Evaluate the strength, limitations, and applicability of available evidence before translating findings into recommendations.
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Communicate analytical findings, research limitations, and recommendations clearly to both technical and nontechnical audiences.
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Proactively identify emerging HOS risks, opportunities, and research questions that could inform future initiatives.
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Facilitate cross-functional discussions related to evidence, targeting strategies, intervention design, and performance improvement.
Requirements
~2 min read-
Bachelor’s degree in a quantitative, behavioral science, social science, or related field with at least 5 years of relevant analytical or applied research experience; or a Master’s or Doctoral degree in a related field with at least 3 years of relevant experience.
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Experience with data manipulation, exploratory analysis, interpretation, and visualization.
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Proficiency in at least one analytical or statistical programming language, such as Python, R, SAS, or SQL.
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Strong written and verbal communication skills, particularly the ability to translate technical findings into clear, actionable insights for nontechnical stakeholders.
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Strong analytical judgment and the ability to select appropriate research or analytical approaches for complex and ambiguous questions.
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Experience assessing evidence quality, identifying limitations, and connecting analytical results to practical business decisions.
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Experience with behavioral science, survey methodology, psychometrics, or member-reported outcomes is preferred.
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Healthcare experience involving Medicare Advantage, Stars, HOS, CAHPS, patient experience, or quality improvement is preferred.
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Experience conducting literature reviews, evidence synthesis, or competitive intelligence is a plus.
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Experience applying research insights to intervention design, consumer outreach, or engagement strategies is preferred.
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Familiarity with predictive models and the ability to interpret model outputs and translate them into operational strategies.
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Experience working with large or complex data environments and visualization platforms such as Databricks or Power BI is advantageous.
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Strong collaboration skills and a passion for using research and analytics to improve consumer experiences.
What We Offer
~2 min readLocation & Eligibility
Listing Details
- First seen
- October 7, 2026
- Last seen
- October 7, 2026
Posting Health
- Days active
- -1
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- October 7, 2026
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