Lead Data Scientist: Claims and Service DS Knowledge & Development Solutions
$120,000–$257,000 year
On-siteSeattle, Washington, United States or Boston, Massachusetts, United States
Job Summary
Own the Generative AI and ML portfolio for Knowledge & Development Solutions by identifying, prioritizing, and delivering AI/ML use cases that improve knowledge discovery, content effectiveness, and employee enablement. Design, build, and evaluate predictive models, GenAI applications, semantic search, and RAG solutions while applying full-stack data science practices from problem framing through deployment and optimization. Partner with stakeholders across Technology, Engineering, Architecture, UX, and Compliance to move solutions from concept to production, defining measurement strategies to assess model performance and business outcomes. Provide technical mentorship on scalable AI/ML implementation patterns and explain complex technical concepts to leadership and product teams.
Required Qualifications
- Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of 8 years of relevant experience
- Broad knowledge of predictive analytic techniques and statistical diagnostics of models
- Advanced knowledge of predictive toolset; reflects as expert resource for tool development
- Demonstrated ability to exchange ideas and convey complex information clearly and concisely
- Ability to establish and build relationships within and outside the organization
- Ability to give effective training and presentations to management and other groups
- Ability to use results of analysis to persuade team, department management or senior management to a particular course of action
- Broad knowledge of business drivers and market context
- Has a value driven perspective with regard to understanding of work context and impact
Desired Qualifications
- Full-stack data science experience, including problem framing, data exploration, modeling, evaluation, deployment partnership, measurement, and optimization
- Expert-level Python development with strong object-oriented design, modular architecture, and engineering best practices
- Proven experience building machine learning, predictive modeling, statistical, Generative AI, or data science solutions that solve real business problems
- Strong understanding of supervised and unsupervised learning ML, experimentation, and evaluation
- Experience with GenAI, LLM-based applications, Q&A, chat, embeddings, prompt engineering, retrieval-augmented generation, or AI-assisted workflows
- Experience working with structured and unstructured data, including operational data, behavioral data, documents, knowledge articles, training materials, communications, or other enterprise content
- Strong ML Ops experience, including experimentation, model lifecycle management, monitoring, observability, governance, and production readiness
- Ability to partner with non-technical stakeholders, understand complex workflows, and translate ambiguous needs into practical, measurable AI/ML solutions
- Strong communication skills with the ability to explain technical concepts clearly to Product, business, engineering, and leadership audiences
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