Job Description

As an AI Strategist within the Chief Data & Analytics Office, you will lead how AI creates measurable business value across Wellabe while staying close enough to technology to turn strategy into working solutions. This role sits at the intersection of business strategy, AI product thinking, data and technology, and responsible innovation. It will translate Wellabe’s Capital, Growth, and Digital priorities into a focused portfolio of AI opportunities, then partner hands-on with cross-functional teams to validate, prototype, implement, and scale the highest-value use cases.

The ideal candidate is a strategist-practitioner: someone who can engage executives on where AI should be applied, build the business case and roadmap, and also work directly with data, models, prompts, prototypes, and AI platforms to determine what will actually work.

What you will accomplish:

• Turn enterprise business priorities into a pragmatic, prioritized AI strategy and roadmap tied to measurable outcomes.
• Accelerate profitable growth, operational efficiency, and better customer and agent experiences through AI.
• Rapidly validate ideas through hands-on experimentation and prototypes before committing to scaled delivery.
• Build reusable AI capabilities and patterns rather than disconnected, one-time solutions.
• Establish trust through responsible AI governance, transparency, human oversight, and measurable performance.
• Increase AI fluency and adoption across business teams.

Core Responsibilities

• Define Wellabe's AI strategy, investment themes, and roadmap aligned with strategic business goals.
• Partner with Business Champions and functional leaders to frame business problems, identify where AI is appropriate, quantify value, and prioritize opportunities.
• Lead cross-functional AI Intelligence Pods from discovery and business case development through experimentation, implementation, adoption, and value realization.
• Operate hands-on during discovery and validation: explore data, develop prompts, test LLM and machine-learning approaches, create proof-of-concepts, evaluate outputs, and help determine technical feasibility.
• Use Python, notebooks, APIs, and AI/ML platforms to prototype ideas, analyze results, and communicate what is technically possible to business and engineering teams.
• Partner with Data Science, Analytics, Data Engineering, Architecture, Security, and IT teams to translate prototypes into scalable, supportable solutions in the Azure and Databricks ecosystem.
• Partner with AI Steering and AI Governance Committees to assess strategic alignment, value, feasibility, risk, readiness, controls, and sequencing.
• Establish reusable methods for AI opportunity assessment, experimentation, evaluation, deployment readiness, adoption, and value measurement.
• Guide responsible AI practices including privacy, security, fairness, explainability, model risk, human oversight, and appropriate use of enterprise data.
• Define KPIs and benefit-tracking approaches for AI initiatives, including baseline performance, adoption, operating impact, revenue or retention impact, and realized ROI where applicable.
• Evaluate AI vendors, foundation models, platforms, and emerging technologies through structured assessments and hands-on testing rather than vendor claims alone.
• Own the lifecycle of existing enterprise AI solutions, including monitoring, enhancement, and stakeholder support.
• Monitor developments in Generative AI, agentic AI, LLMs, conversational AI, predictive modeling, and intelligent automation and translate relevant developments into actionable recommendations for Wellabe.
• Serve as an executive-facing thought partner and a practitioner-level collaborator who can explain AI trade-offs clearly to both business leaders and technical teams.

Qualifications

• Working knowledge of traditional machine learning concepts including supervised learning, feature engineering, model performance metrics, explainability, monitoring, and model lifecycle management.
• Experience with cloud AI ecosystems, preferably Microsoft Azure and Databricks, including familiarity with MLflow and enterprise model/LLM lifecycle practices.
• Strong understanding of the insurance value chain, ideally including underwriting, claims, actuarial/pricing, policy administration, distribution, customer service, and retention.
• Ability to build business cases, define value hypotheses and KPIs, compare solution alternatives, and communicate technical and economic trade-offs to senior leaders.
• Ability to balance innovation with governance, security, privacy, compliance, and model risk expectations in a regulated environment.
• Exceptional communication and facilitation skills with the ability to influence executives, business leaders, product teams, and technical practitioners.
• What success looks like:
• A small number of high-value AI priorities are clearly linked to Wellabe strategy and advanced with discipline.
• AI ideas are validated quickly with evidence before significant delivery investment is made.
• Prototypes transition into scalable capabilities through effective partnership with data engineering and technology teams.
• AI solutions achieve measurable adoption and business impact, not simply technical deployment.
• Reusable patterns, governance, and organizational AI capability improve with each use case.
• 7+ years of experience spanning AI/ML, AI strategy, product management, analytics, or digital transformation, with 3+ years in insurance or financial services required.
• Proven ability to define AI strategies and roadmaps and move initiatives from problem framing through experimentation, delivery, adoption, and measurable business outcomes.
• Demonstrated hands-on AI/ML development experience, with the ability to independently build, test, and evaluate working prototypes in Python, including predictive models and AI/ML workflows, and clearly communicate model performance, assumptions, limitations, and business implications to technical and non-technical audiences.
• Practical experience developing Generative AI and LLM solutions, with the ability to independently prototype and evaluate approaches such as prompt engineering, RAG, embeddings/vector search, structured outputs, and AI agents, and assess their effectiveness, limitations, and suitability for production use.

Education

• Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Business, or a related field.
• Advanced degree, such as an MBA or MS or equivalent advanced experience preferred.

Benefits

• Hybrid availability
• 401(k) with company match
• Health insurance
• Paid time off, holidays
• Volunteer time off
• Lifestyle Spending Account (LSA)
• Paternity leave

Growth opportunities

We believe each of us has potential to grow and adapt with our business. We take your career as seriously as you do. Helping you develop your skills and talents leads to opportunities — not only for you, but also for our company. That’s why we provide:

• LinkedIn Learning Premium access
• CliftonStrengths® assessment and coaching
• On-site and virtual workshops and cohorts featuring world-class content from FranklinCovey, Crucial Learning, Gallup, and more
• Free world-class insurance acumen courses through AHIP and LOMA
• Reimbursement and bonus opportunities for professional designations and certifications, including a tuition reimbursement program
• Opportunities to take part in Wellabe's mentorship programs

About Wellabe

Since 1929, Wellabe has been finding solutions to help our customers protect their health and financial well-being. And we’re committed to fostering an internal culture of inclusivity, well-being, and development so each of our team members can succeed. Learn more about Wellabe’s culture of betterment by visiting wellabe.com/culture.

Wellabe is full of smart, caring, hard-working people with a broad range of talents who understand collaboration is key. We bring our best selves every day, to connect with others to solve problems, spark innovation, and bring ideas to life. Meet the team and learn what makes Wellabe a great place to work by visiting wellabe.com/news/employee-spotlights.

Our core values:

• Be dedicated: Show unwavering commitment by proactively taking initiative, setting clear goals, and managing time effectively.
• Be trustworthy: Take accountability for actions, navigate difficult conversations with integrity, and build strong relationships through consistent, honest behavior.
• Be determined: Demonstrate enthusiasm and a relentless drive to overcome obstacles and achieve goals.
• Be collaborative: Foster teamwork by being self-aware, actively listening, and effectively communicating across all levels.
• Be open: Embrace diversity and new ideas to create an inclusive environment.
• Be generous: Embody generosity and compassion by serving a greater purpose and helping others.
• Be better: Commit to continuous improvement and adapt effectively to change.
• Be well: Prioritize physical and mental health, manage stress, and demonstrate emotional intelligence.