Principal Data Scientist

Role Description

This Principal Data Scientist role will be a part of the Decision Sciences team in Client Center of Excellence organization. The role will be responsible for strategic interpretation of data and business requirements to provide executive leadership and the growth with customer centric data driven insights and AI/ML solutions. Working in collaboration with Director, Decision Sciences and other data scientists team members, this role works to:

• Identify new business requirements across the organization.
• Translate business requirements into data models.
• Perform data engineering to combine diverse data sets.
• Develop custom algorithms for predictive AI models to support the Growth business and Optum business units.

You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

• Lead development of advanced AI/ML systems using techniques such as deep learning, representation learning, time-series modeling, survival analysis, and probabilistic modeling to solve complex healthcare problems.
• Develop Generative AI and LLM-powered solutions including retrieval-augmented generation (RAG) pipelines, domain-adapted LLMs, and AI copilots for enterprise workflows.
• Lead collaboration with key business stakeholders to develop business solutions based on data driven insights to solve complex business problems.
• Lead projects that combine diverse customer data sets to identify trends and opportunities, develop custom machine learning models, and provide recommendations to optimize the business and address data-related problems.
• Serve as a senior technical authority in AI/ML by mentoring data scientists and reviewing complex modeling approaches and architecture.
• Coordinate with different functional teams to improve customer data architecture, ensure accuracy of model output and implement new data gathering processes.
• Create customized summaries, business presentations and documentation for internal business clients based on the results of research.
• Collaborate with engineering, platform, and product teams to operationalize scalable AI/ML and GenAI systems within enterprise platforms.

Qualifications

• 8+ years of experience in machine learning, artificial intelligence, or applied data science to develop data products in a business environment.
• 8+ years of experience in Python-based machine learning development using frameworks such as PyTorch, TensorFlow, Pandas or equivalent.
• 5+ years of experience designing and deploying production machine learning systems leveraging regression, natural language processing algorithms, classification and clustering, time-series forecasting and predictive/prescriptive modeling.
• 5+ years of experience providing data driven solutions, predictive models, reports, or recommendations within a business environment using SQL or data visualization tools.

Requirements

• Experience working with distributed ML systems and large-scale data platforms such as Snowflake, Spark, Databricks, or other ML systems.
• Experience working as a project or team lead on the development of data products in a business environment.
• Experience working as a key SME to executive or C-Suite stakeholders.
• Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP.
• Experience working with healthcare datasets and standards such as claims, EHR, ICD, CPT, SNOMED, FHIR, or HL7.
• External contributions such as publications, patents, or open-source projects in machine learning or generative AI.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase.
• 401k contribution (all benefits are subject to eligibility requirements).