Sr Analyst, AI Transformation
EvolentAbout the role
Your Future Evolves Here
Evolent partners with health plans and providers to achieve better outcomes for people with most complex and costly health conditions. Working across specialties and primary care, we seek to connect the pieces of fragmented health care system and ensure people get the same level of care and compassion we would want for our loved ones.
Evolent employees enjoy work/life balance, the flexibility to suit their work to their lives, and autonomy they need to get things done. We believe that people do their best work when they're supported to live their best lives, and when they feel welcome to bring their whole selves to work. That's one reason why diversity and inclusion are core to our business.
Join Evolent for the mission. Stay for the culture.
What You’ll Be Doing:
About the Role
The Senior Analyst, AI Transformation is a hands-on builder who designs and deploys AI-enabled analytics workflows. This role blends analytics engineering, automation, and practical AI implementation. This role works directly on the technical execution of transformation initiatives—building data pipelines in Microsoft Fabric, engineering prompts for Azure OpenAI, developing automation scripts for reporting and compliance workflows, and maintaining the tools and infrastructure that power self-service analytics and client value intelligence systems.
You will help measure impact and maintain documentation that supports software development capitalization requirements.
What You’ll Be Doing
- Build Microsoft Fabric pipelines and consolidated Lakehouse models.
- Develop certified views with reconciled metric definitions.
- Engineer Azure OpenAI prompts for narrative and insight generation.
- Build Python-based automation for reporting and compliance workflows.
- Support self-service analytics platforms with text-to-SQL and routing logic.
- Implement automated compliance and validation checks.
- Build signal detection and alerting pipelines.
- Track and analyze AI-driven program effectiveness.
- Maintain build logs and time tracking aligned to ASC 350-40.
- Create Copilot prompt playbooks and best practices.
- Monitor pipeline health and resolve data issues.
- Support Power BI automation and DAX libraries.
Required Experience:
- Bachelor’s degree in a quantitative field (computer science, data science, statistics, mathematics, engineering) or healthcare-related discipline.
- At least 3 years of professional experience in analytics engineering, data engineering, or applied AI/ML development.
- Strong proficiency in Python (pandas, FastAPI, API integrations) and SQL (complex joins, window functions, CTEs across multiple database platforms).
- Experience with cloud data platforms, particularly Microsoft Azure (Azure Data Factory or Fabric, Azure SQL, Azure OpenAI or similar LLM APIs).
- Prompt engineering and LLM integration experience, including structured output generation and iterative prompt optimization.
- Proficiency with Power BI and DAX; ability to build and troubleshoot reports and measures programmatically.
- Experience with healthcare claims data, and healthcare-specific data structures.
- Strong problem-solving abilities with a track record of building and deploying production-grade data pipelines and automation tools.
- Ability to work independently with limited oversight while coordinating effectively with cross-functional teams.
- Strong documentation practices, including the ability to maintain clear project logs, metric definition documents, and pipeline architecture records.
Preferred Experience:
- Master’s degree in data science, computer science, or a related quantitative field.
- Experience with Microsoft Fabric specifically (Data Factory pipelines, Lakehouse, Spark notebooks).
- Familiarity with python-pptx, openpyxl, or similar programmatic document generation libraries.
- Experience with text-to-SQL systems or natural language interfaces to databases.
- Knowledge of healthcare reimbursement (DRGs, CPT, RVUs) and utilization management analytics.
- Experience with DevOps tooling (Azure DevOps, Git, CI/CD pipelines).
- Familiarity with capitalizable labor documentation under ASC 350-40 or similar frameworks.
- Background in healthcare payer, managed care, or specialty risk-bearing organizations.
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