Summary:

In this role, you willdevelop and deploy advanced analytics, machine learning, generative AI, and agentic AI solutions that address complex business and client challenges. You will design scalable data science products, translate sophisticated analytical findings into actionable insights, and guide data scientists in delivering high-quality solutions that improve clinical, operational, and economic outcomes. You will influence technical strategy, drive innovation, and ensure analytical solutions align with organizational objectives.

Responsibilities:

Lead the design, development, and implementation of advanced machine learning, generative AI solutions across structured and unstructured data.\nBuild and deploy scalable, automated data science products and reusable analytic assets that support business and client objectives.\nAnalyze large-scale, high-dimensional datasets using modern analytics tools and distributed computing platforms to identify trends, opportunities, and actionable insights.\nDesign and prototype agentic AI workflows leveraging large language models (LLMs), retrieval systems, structured data, APIs, tools, and business rules to automate complex business processes.\nTranslate business requirements into AI agent architectures, including task decomposition, tool orchestration, routing logic, escalation paths, and human approval checkpoints.\nOptimize retrieval-augmented generation (RAG) solutions through embedding evaluation, metadata design, reranking approaches, citation quality assessment, and knowledge freshness validation.\nDevelop evaluation frameworks for machine learning and AI solutions, including performance, accuracy, reliability, hallucination risk, latency, cost, safety, and consistency measures.\nMake key analytical and architectural decisions, establish technical standards, and provide leadership on methodology, model selection, solution design, and AI implementation best practices.\nLead code reviews, mentor data scientists, and promote best practices in software development, responsible AI, model governance, and analytics delivery.\nPartner with engineering, platform, and business teams to deploy, monitor, and maintain production-ready analytics and AI solutions.\nTranslate complex analytical findings into clear reports, visualizations, and presentations for technical and non-technical audiences.\nCollaborate with stakeholders and clients to define analytical approaches that address strategic, operational, and clinical objectives.\nEvaluate emerging technologies and industry trends to advance organizational analytics and AI capabilities.

Qualifications:

Relevant degree preferred. Advanced degree in applied mathematics, statistics, computer science, econometrics, or a related field is a plus.\n7 or more years of relevant experience required.\nDemonstrated expertise in data science methodologies, statistical modeling, machine learning, generative AI, agentic AI, and natural language processing required.\nStrong understanding of large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and autonomous decision-making frameworks within enterprise AI environments highly preferred.\nExpertise in programming languages such as Python, R, SQL, SAS, or similar analytical tools.\nExperience with vector databases, semantic search technologies, knowledge graphs, metadata management, or enterprise search platforms.\nExperience deploying, monitoring, and maintaining machine learning and AI solutions in production environments.\nKnowledge of responsible AI principles, model governance, explainability, bias detection, validation methodologies, and ethical use of data.\nExperience designing and implementing human-in-the-loop workflows that balance automation, governance, risk management, and user oversight.\nExperience working with cloud-based and distributed data platforms and modern analytics frameworks such as Databricks.\nStrong analytical, problem-solving, communication, and presentation skills with the ability to convey complex concepts to diverse audiences.\nExperience leading complex analytics initiatives, providing technical guidance, and mentoring data scientists.\nExperience working with healthcare data, including clinical, claims, operational, or financial datasets preferred. #LI-JB1

Estimated Hiring Range:

At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $117,600.00 to $206,000.00. This position is also incentive eligible. Vizient has a comprehensive benefits plan!

Please view our benefits here:

http://www.vizientinc.com/about-us/careers

Equal Opportunity Employer:

Females/Minorities/Veterans/Individuals with Disabilities The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.","accountId","44026641","Vizient, 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Lead Data Scientist