Data Scientists - Remote

UnitedHealth Group•Minnetonka, MN

1d•Remote

About The Position

At UnitedHealthcare, we’re simplifying the health care experience, creating healthier communities and removing barriers to quality care. The work you do here impacts the lives of millions of people for the better. Come build the health care system of tomorrow, making it more responsive, affordable and optimized. Ready to make a difference? Join us to start Caring. Connecting. Growing together This Data Scientist is the first of its kind and critical role for accelerating the AI agenda across UHC Consumer Operations. This position will report to the Sr Director Data AI Program Management, Governance and Data Integrity. This position combines data science with healthcare innovation, AI ethics, and regulatory compliance, providing a unique opportunity to help shape the future of AI applications in healthcare. In this role, you will collaborate with cross-functional teams to refine AI methodologies, develop and validate robust testing protocols to identify potential model failures. A successful candidate will interact with diverse teams using a wide variety of AI methods and validate test plans and results. They will design and oversee testing and monitoring plans for novel use cases across a wide spectrum of types of AI and healthcare applications. The role will participate in UHG’s external industry groups involve with AI policy. The role requires ability to write clear documentation on use-case specific testing requirements. You will also engage with stakeholders to advocate for and drive the adoption of responsible AI practices, providing a unique opportunity to shape the future of ethical AI applications in healthcare. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

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