Data Scientist – CAHPS Analytic

🕒 2 days ago

🇺🇸 United States – Remote

💵 $149.9k - $224.8k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

📊 Data Scientist

👻 Ghost score 10%

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Logo of Alignment Health

Alignment Health

501 - 1000 employees

Founded 2013

⚕️ Healthcare Insurance

🛡️ Insurance

🏥 Healthcare

💰 $135M Series C on 2020-03

Healthcare Insurance • Insurance • Healthcare

Alignment Health is dedicated to providing comprehensive care for Medicare members, emphasizing the needs of seniors, the chronically ill, and those who are frail. With a mission to transform senior healthcare, Alignment Health leverages a tailored care model and advanced technology to deliver high-quality, low-cost healthcare services. Their 24/7 concierge care team collaborates with trusted local providers to ensure that every member receives personalized care, reflecting the company's commitment to treating all members as valued family members.

📋 Description

• Collaborate with Stars, member experience, and operations leaders to understand CAHPS performance drivers and translate them into analytical solutions • Segment members by likelihood to respond to the CAHPS survey and predicted satisfaction • Build and fine-tune models predicting member-level risk of low CAHPS domain scores • Analyze item-level CAHPS survey data to identify survey questions driving measure performance • Build pipelines tracking CAHPS survey administration cycles, sampling, fielding, and response rates • Validate case-mix adjustment logic against CMS/NCQA methodology • Model statistical significance and year-over-year variance to distinguish performance shifts from survey noise or sampling error • Coordinate with CAHPS survey vendors on sampling methodology, fielding timelines, and case-mix adjustment specifications • Collaborate with engineering teams to version, test, and deploy models using Git, CI/CD pipelines, and VM environments • Partner with member experience, call center, provider network, Compliance, and Legal teams to align outputs and interventions with CMS guidance • Build dashboards tracking CAHPS performance against Star Rating cut points and prior-year trends • Help standardize definitions, documentation logic, and reporting workflows for enterprise-wide CAHPS analytics

🎯 Requirements

• 2+ years of relevant experience in predictive modeling and analysis, with demonstrated application to survey-based or member experience data • Required PhD in Computer Science, Engineering, Mathematics, Statistics, or a related field • Demonstrated experience with CMS/NCQA CAHPS survey methodology, including case-mix adjustment, sampling and fielding cycles, and item response theory or other psychometric methods • Working knowledge of individual CAHPS measure domains • Working knowledge of CMS Star Ratings procedures • Experience building end-to-end data science solutions and applying machine learning methods to real-world problems with measurable outcomes • Solid data structures and algorithms background • Strong programming skills in Python, Java, R, Scala, or C++ • Demonstrated proficiency in SQL and relational databases • Experience with data visualization and presentation • Experience setting experimental or analytical frameworks for complex, ambiguous scenarios • Understanding of confidence intervals, significance of error measurement, and development/evaluation data sets • Experience manipulating and analyzing complex, high-volume, high-dimensionality, and unstructured data from varying sources • Preferred: Healthcare experience, particularly within Medicare Advantage • Preferred: Experience applying NLP techniques to open-ended survey comment analysis • Preferred: Experience in cloud ecosystems such as Azure or AWS • Preferred: Published work related to survey methodology, psychometrics, or member experience measurement • Demonstrable track record dealing well with ambiguity, prioritizing needs, and delivering results in an agile, dynamic environment

🏖️ Benefits

• Equal Opportunity/Affirmative Action Employer • Reasonable accommodations for individuals with disabilities

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