Job DescriptionWhat Will I be Doing?
The Lead Data Scientist, AI Engineering sets technical direction for advanced analytics, machine learning, and applied AI that improve business performance and member/guest experience at Hilton Grand Vacations. This role designs and delivers analytical products and AI-powered solutions-from classical prediction and recommender systems to LLM-orchestrated pipelines, agents, and generative experiences-on Databricks and the broader Azure stack.
Primary domains include Inventory Management, Sales Efficiency, Marketing, Member/Guest Satisfaction, Operational Reporting, and Digital Analytics, with extensions into Pricing, Portfolio performance, and personalized member/guest experiences. The Lead partners with MLOps, Operational Reporting, IT, and product stakeholders to define scalable patterns for model and AI application lifecycle management, governs quality and risk for production assets, and elevates delivery quality across the analytics community
Responsibilities- Define and prioritize an analytics, ML, and AI engineering roadmap; translate business strategy into a portfolio of models, experiments, LLM applications, and analytical products with clear success metrics.
- Lead end-to-end delivery of complex ML, statistical, and generative AI solutions-from problem framing and data strategy through deployment, monitoring, evaluation, and iteration-in partnership with MLOps and engineering.
- Build and evolve an extensible data science and AI platform on Databricks (Python, SQL, Databricks ML, Model Serving, Asset Bundles) integrated with Azure OpenAI and related services.
- Design and ship applied AI systems relevant to IMA work: prompt and context engineering, LLM orchestration pipelines (e.g. KPI narrative media/HTML), retrieval-augmented generation (RAG) where appropriate, evaluation harnesses, guardrails, and Copilot/agent workflows that automate operational processes.
- Own architecture and standards for forecasting, recommender/personalization systems, predictive analytics, and production AI apps; ensure reproducibility, documentation, CI/CD readiness, and operational excellence.
- Identify revenue and efficiency opportunities using advanced analytics and AI; initiate projects that bridge operational metrics to financial and customer outcomes.
- Provide a feature store, reusable components, and technical support that accelerate other analytics teams.
- Mentor and coach data scientists and analysts through design reviews, code reviews, and pairing-raising the bar on experimentation, responsible AI, and production quality-without formal supervisory responsibility.
- Respond quickly to high-impact ad-hoc requests; deliver actionable insights and clear recommendations to leadership.
- Perform prediction modeling, customer lifetime value, and related analyses that inform strategy.
- Ensure MLOps / AIOps discipline: maintain production code and assets, monitoring, retraining/refresh patterns, incident response, and reliability for models and generative pipelines.
- Represent IMA analytics with senior business and technology stakeholders: set expectations, manage trade-offs, and communicate implications for operations and financial outcomes.
- Participate in data governance-metrics definitions, data quality, and source improvement-and formulate UX strategies so analytical and AI outputs are adopted by end users.
- Perform additional project-based and ad-hoc analysis as assigned.
QualificationsTo fulfill this role successfully, you must possess the following minimum qualifications and experience: - Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.
- 8+ years of experience in data science, machine learning, advanced analytics, or AI engineering, including substantial hands-on model/application development in production environments (candidates with 5-7 years of exceptional production AI/ML delivery will be considered).
- Minimum of 3 years of hands-on experience with Python, SQL, and Databricks (or equivalent lakehouse platforms).
- Proven experience with NLP and/or generative AI technologies (e.g. OpenAI / Azure OpenAI) applied to real business problems.
- Experience with MLOps and maintaining production code, models, and AI pipeline assets.
- Demonstrated ability to mentor peers, lead technical reviews, and set standards-without requiring prior people-manager experience.
- Strong communication skills; ability to present technical concepts to non-technical stakeholders.
- Ability to quickly address ad-hoc requests and deliver actionable insights.
- Proficiency in English, verbal and written.
It would be advantageous in this position for you to demonstrate the following capabilities and distinctions: - Masters degree or PhD in a quantitative or computer science discipline.
- Hospitality, travel, or membership-club analytics experience; timeshare / vacation ownership domain a plus.
- Pricing optimization, inventory management, marketing analytics, or sales-efficiency modeling.
- Real-time recommendation, personalization, or API-driven model consumption.
- Databricks Asset Bundles, Azure DevOps pipelines, enterprise data platforms, and feature-store patterns.
- Building customer-facing or internal generative experiences (narrated briefings, personalized HTML/content pipelines, TTS/media generation, chat or triage agents via Copilot Studio / Power Platform / custom apps).
- Experience with FastAPI, React, or Databricks Apps for operational AI products.
- Power BI, Cognos, or similar BI tools; generative BI exploration.
- Prior technical lead, principal, or staff-level experience (formal people management is not required).
