Hybrid Data Scientist – Health Plan Operations

at myPlace Health

• Job title: Data Scientist – Health Plan Operations
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $129,767 - $165,274 per year
• Degree requirement: Postgraduate Degree
• Tech skills: AWS, Azure, Cloud, Python, Spark, SQL, Tableau
• Location requirements: Hybrid, Los Angeles, United States

About the role

• Risk Adjustment Data Scientist at myPlace Health partnering with leaders to design innovative data-driven solutions. Building predictive models and empowering teams with actionable healthcare insights.

Responsibilities

• Shape High-Impact Solutions: Partner closely with our business and clinical leaders to uncover the most valuable challenges in risk adjustment and craft innovative, data-driven solutions.
• Bring Data to Life: Design and deploy predictive models that estimate risk scores and highlight anomalies across patient populations—empowering smarter, more proactive care.
• Build Strong Data Foundations: Contribute to robust data pipelines and scalable model infrastructure in Microsoft Fabric—integrating both structured and unstructured data to support our growing organization.
• Collaborate to Deliver: Work hand-in-hand with Product and Operations teams to create production-ready models using version-controlled workflows, CI/CD practices, and cloud environments that ensure reliability and agility.
• Illuminate the Journey: Track and analyze the full lifecycle of risk-adjustment submissions—including encounter data, EDPS, and RAPS—leveraging knowledge of CMS documents (MAO-004, MOR, MMR) to ensure accuracy and compliance.
• Turn Data Into Stories: Build intuitive dashboards in Power BI that transform complex data into clear, actionable insights for leaders and decision-makers across the organization.
• Drive Better Engagement: Monitor physician performance in risk-adjustment workflows, surfacing trends in documentation practices and coding accuracy while identifying opportunities for education and workflow optimization.
• Standardize for Scale: Develop consistent documentation logic, definitions, and reporting workflows that enable enterprise-wide analytics and improve operational efficiency.
• Simplify the Complex: Translate intricate data findings into meaningful, actionable insights that Operations, Clinical, and Finance teams can easily understand and apply.
• Pitch In Where Needed: Contribute to additional projects and priorities as they arise—bringing a collaborative mindset and problem-solving approach to new challenges.

Requirements

• A Strong Educational Foundation: Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Proven Real-World Impact: 4+ years of experience applying machine learning and predictive modeling to solve meaningful problems.
• Hands-On Coding Expertise: Proficiency in Python (preferred) or R, with the ability to design and deliver end-to-end data science solutions.
• Data Wrangler Skills: Strong experience using SQL to query and transform large-scale healthcare data into insights that matter.
• Technical Rigor: Solid understanding of data structures, algorithms, and software engineering best practices.
• Advanced Machine Learning Know-How: Deep knowledge of techniques including predictive modeling, classification, and natural language processing.
• Healthcare Data Savvy: Experience analyzing large, complex datasets such as claims, EMR, enrollment, and operational data.
• Insight Translator: Proven ability to turn complex analysis into clear, actionable insights for both technical and non-technical stakeholders.
• Effective Communicator: Excellent written and verbal communication skills with a collaborative, problem-solving mindset.
• Risk Adjustment Expertise: Hands-on experience with healthcare risk adjustment models like CMS-HCC, PACE, or Medicare Advantage.
• Healthcare Data Familiarity: Knowledge of critical datasets including 837 files, EMR, and eligibility data.
• Workflow Awareness: Understanding of physician engagement processes that support coding accuracy and documentation excellence.
• Big Data Proficiency: Experience with technologies such as Spark, Fabric, Databricks, or Snowflake.
• Cloud Environment Experience: Comfortable working in platforms like Azure, AWS, or similar ecosystems.
• Visual Storytelling Skills: Skilled in using tools like Power BI, Tableau, or similar to present insights with clarity and impact.
• Startup-Ready Spirit: Adaptable, curious, and energized by the opportunity to thrive in a fast-growing, dynamic environment.

Benefits

• Competitive Pay & Total Rewards
• Performance-Based Incentives
• Ongoing Growth & Feedback
• Plan for Your Future
• Health Coverage that Fits Your Life
• More Than Just Medical
• Generous Time Off
• Support for Your Learning
• Family Comes First