Director of Applied AI

IHG • Atlanta, GA

1d • $160,000 - $220,000 • Hybrid

About The Position

IHG is seeking a Director, Applied AI to lead its Data Science team’s work across forecasting, predictive modeling, optimization, ModelOps, and GenAI. The role sets strategy, prioritizes high-value opportunities, and builds reusable capabilities that improve business decisions and deliver measurable impact. It centralizes efforts in non-guest predictive modeling and forecasting; shared ModelOps, MLOps, and LLMOps capabilities and standards; and GenAI and agentic solutions for analytics and business productivity.

The Director manages, hires, leads, and develops applied scientists and AI/ML specialists, including managers and senior technical talent. The role defines standards for scientific rigor, engineering practices, documentation, and business communication, and develops capability across teams through mentoring, technical reviews, and shared standards. The Director partners with senior leaders and stakeholders across business, product, technology, governance, P&T, Data Engineering, and vendor teams to communicate priorities, progress, risks, and business impact and to support adoption and reliable operations.

The position owns the Applied AI roadmap and portfolio process; leads the development of GenAI analytics products, conversational analytics, analyst copilots, and agentic workflows; and delivers forecasting and predictive solutions for commercial planning, demand, revenue, operations, and performance management. It also owns shared ModelOps practices, establishing standards and capabilities for deployment, evaluation, monitoring, operational readiness, and scale. The role is based on a hybrid schedule requiring three days per week in IHG’s Atlanta office, subject to business needs, with limited travel of 10%.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Engineering, MIS/IT, or a related field, or equivalent experience.
• 10+ years in applied machine learning, analytics engineering, or data science.
• 3+ years leading managers or multidisciplinary teams.
• Demonstrated experience delivering production AI solutions and maintaining their performance over time.
• Strong business forecasting experience, including backtesting and communicating uncertainty.
• Experience building analytical products that achieve sustained adoption.
• Expert Python and SQL skills, with strong data modeling and analytics fundamentals.
• Experience with statistical and machine learning forecasting, hierarchical/time-series evaluation, and scenario modeling.
• Experience building GenAI solutions on structured enterprise data, with explainability and traceability to source data.
• Experience with unstructured text and speech analytics, including classification, theme extraction, and summarization.
• Strong understanding of MLOps and LLMOps, including evaluation, monitoring, observability, and operational readiness.
• Strong product judgment, including problem framing, success measures, and adoption plans.

Responsibilities

• Own the Applied AI roadmap and establish processes for intake, prioritization, delivery, and measurement.
• Translate business needs into opportunities for predictive modeling, forecasting, optimization, and GenAI.
• Prioritize the portfolio based on business value, feasibility, data readiness, and adoption.
• Build reusable capabilities and standards to move successful solutions from experimentation into production.
• Partner with business leaders to define success measures and integrate solutions into operating workflows.
• Lead development of GenAI analytics products that provide accurate, explainable answers grounded in governed data products, including structured Data Analytics Products (DAPs).
• Develop conversational analytics and analyst copilots that help users investigate metric changes, drivers, segment shifts, channel mix, and anomalies.
• Produce data-grounded outputs such as tables, charts, narratives, hypotheses, and recommended next analyses.
• Develop insights from unstructured sources such as reviews, surveys, and call transcripts, including themes, sentiment, contact reasons, and friction points.
• Build agentic workflows to improve productivity, automate recurring analytical work, and support business decision-making.
• Establish GenAI evaluation and release standards covering accuracy, grounding, traceability, consistency, and usability.
• Lead applied AI and forecasting solutions for commercial planning, demand, revenue, operations, and performance management.
• Develop forecasting products for outcomes such as revenue, occupancy, demand, and aggregate co-brand spend.
• Combine statistical forecasting and machine learning to capture seasonality, business drivers, events, promotions, and nonlinear relationships.
• Develop scenario and what-if capabilities that help stakeholders evaluate alternatives and understand uncertainty.
• Establish backtesting, baseline comparisons, performance monitoring, and appropriate prediction ranges.
• Deliver documented, reusable products that support recurring planning and decision-making.
• Own shared ModelOps practices for machine learning and GenAI solutions within the data science organization.
• Establish foundations for versioning, testing, CI/CD, deployment, monitoring, alerting, and model refresh.
• Define operational readiness standards and monitor model performance, drift, calibration, and stability.
• Build GenAI evaluation capabilities covering groundedness, retrieval quality, output consistency, guardrails, cost, and latency.
• Work with P&T, Data Engineering, and vendor partners to implement and operate ModelOps and LLMOps capabilities.
• Reduce time to production and rework through reusable templates, tooling, playbooks, and coaching.
• Hire, lead, and develop a team of applied scientists and AI/ML specialists, including managers and senior technical talent.
• Define standards for scientific rigor, engineering practices, documentation, and business communication; build capability through mentoring, technical reviews, and shared standards.
• Partner with senior leaders and cross-functional stakeholders to communicate priorities, progress, risks, and business impact and support adoption and reliable operations.

Benefits

• Impressive room discounts across IHG properties.
• Recharge days.
• Volunteering days throughout the year.
• Wellbeing support through the myWellbeing framework, including health, lifestyle, and workplace wellbeing.
• A unique and inclusive culture focused on belonging, growth, and making a difference.

What This Job Offers

• Job Type: Full-time
• Career Level: Director