Data Scientist - Remote

UnitedHealth Group•Minnetonka, MN

1d•$91,700 - $163,700•Remote

About The Position

This Data Scientist role is a critical and first-of-its-kind position for accelerating the AI agenda across UHC Consumer Operations. The role combines data science with healthcare innovation, AI ethics, and regulatory compliance, offering a unique opportunity to shape the future of AI applications in healthcare. The position will report to the Sr Director Data AI Program Management, Governance and Data Integrity. The successful candidate will collaborate with cross-functional teams to refine AI methodologies, develop and validate robust testing protocols to identify potential model failures, and interact with diverse teams using a wide variety of AI methods. They will design and oversee testing and monitoring plans for novel use cases across a wide spectrum of AI and healthcare applications. The role will also participate in UHG’s external industry groups involved with AI policy and requires the ability to write clear documentation on use-case specific testing requirements. Additionally, the candidate will engage with stakeholders to advocate for and drive the adoption of responsible AI practices, shaping the future of ethical AI applications in healthcare.

Requirements

8+ years of experience in computer science, applied mathematics, applied statistics, linguistics or related quantitative fields
Experience in establishing data integrity and governance frameworks at scale
Extensive experience with advanced natural language processing models and clinical natural language processing, clinical de-identification, and clinical annotation
Deep understanding of AI ethics and fairness considerations
Proficiency in the full machine learning lifecycle including development, deployment, and monitoring
Proven solid analytical and problem-solving skills
Legally authorized to work in the US without any restrictions. Proof will be required.

Nice To Haves

Experience collaborating with cross-functional teams including product managers and business stakeholders
Experience partnering with AI forward companies like Amazon, Google, Microsoft and the likes
Knowledge of large language models, conversational AI, prompt engineering, and adversarial testing
Familiarity with regulatory frameworks relevant to AI healthcare systems including claims payment and call centers
History of delivering production systems that include clinical natural language processing, sentiment analysis, text classification, medical/health informatics, clinical de-identification, and clinical annotation
Proven ability to translate business needs into technical solutions

Responsibilities

Design and write new guidelines for AI testing and ongoing monitoring
Design and document improved testing methodologies, especially for novel use cases
Clearly communicate with diverse teams including legal, compliance, and AI development over a wide variety of AI methods including Generative AI and traditional ML
Document findings, create reports related to KPOs, and present results to stakeholders
Develop job aids and guidance documentation for best practices of responsible AI
Help identify vulnerabilities related to PII/PHI exposure in AI interactions
Stay abreast of the latest developments in AI/ML research and incorporate relevant findings into work
Be in lock step with AI strategy counterpart in delivering against AI strategy and product vision and roadmap that is focused on company goals and consumer needs
Support AI program office, setting clear priorities, success metrics and cross functional alignment
Build and enforce consistent AI lifecycle management process (ideation, model development, testing, deployment, monitoring, retirement) including rinse and repeat playbook for AI Review Board (AIRB)
Enforce policies for data quality, lineage, accuracy and security across AI pipelines
Build in partnership with data engineering and platform teams best-in-class data models and maintenance programs to set the foundation for scalable AI growth
Establish data validating protocols to reduce the risk of integrity related incidents
Build, converge and deliver data API’s that prevent data drift, model decay and data hygiene related risks
Design and oversee AI performance reporting dashboards covering accuracy, bias, fairness, operational health, real time anomaly detection and more
Establish and lead the AI incident management framework, including severity levels, response times and escalation protocols
Drive adoption of AI risk management practices
Support key priorities of increasing employee and management engagement by promoting Our United Culture and DEI concepts and activities with leaders and within the organization