Senior Director, Consumer Data Science – Strategy

Role Overview

• Translate business challenges into solvable AI/ML solutions, formulate different approaches, outline pros and cons for each approach, get alignment with business leaders on approaches, deliverables, and delivery timeline.
• Work closely with business teams to develop complex AI/ML algorithms and predictive models to evaluate scenarios and potential future outcomes; leverage problem solving / analytical skills, quantitative expertise, programming and data analysis to identify potential risks related to existing scenarios as well as new products and develop methodologies for tracking and reporting them.
• Collaborate with digital product, marketing, revenue management, operations, finance, and customer experience teams to translate insights into measurable business outcomes.
• Be the subject matter expert and thought leader in building customer data capturing, hosting, business use cases deployment.
• Present strategy, findings and recommendations to senior executives in a clear, compelling manner.
• Perform analyses of structured and unstructured data to solve multiple and complex business problems. Apply analytical rigor & AI/ML methods to analyze large amounts of data.
• Design, build, and deploy machine learning models supporting personalization, pricing optimization, demand forecasting, guest segmentation, and operational efficiency.
• Interact with internal and external peers and management to share highly complex information related to areas of expertise and/or to gain acceptance of new or enhanced technology / business solutions.
• Evaluate and implement emerging methodologies in AI/ML, NLP, recommendation systems, forecasting, and optimization.
• Enhance the team’s modeling toolkit by exploring new algorithms, tools, and frameworks.
• Contribute to the evolution of the company’s machine learning platform, feature stores, and MLOps ecosystem.
• Ensure models are interpretable, ethical, unbiased, and aligned with data governance and privacy standards.
• Maintain rigorous documentation and reproducible workflows.
• Conduct A/B testing, uplift modeling, attribution modeling, and statistical experimentation to validate impact.
• Recruit, mentor, and build a high-performing team of AI/ML consultants with diverse skill sets.
• Foster a collaborative and innovative team culture.
• Mentor junior data scientists and analysts; help establish best practice standards across the data science community.
• Collaborate with engineering to operationalize models via production pipelines, APIs, or real-time systems.
• Partner with data engineering and architecture teams to improve data quality, accessibility, and scalability.
• Adheres to Company standards and maintains compliance with all policies and procedures.

Requirements

• MS or PhD degree in quantitative studies, such as Statistics, Math, Operation Research, Economics, Advanced Analytics, Computer Science, Engineering
• Strong quantitative and analytics background, including advanced-level skillset in predictive modelling, statistical analysis, machine learning, generative AI models, geo-spatial analytics, time series forecasting, optimization.
• 15+ years’ professional experience working in Financial Services, Insurance, Hospitality and Retail industries on applying data science and analytics in sales and marketing applications.
• Familiarity with digital marketing ecosystem.
• Extensive experience in email marketing, digital marketing, and call center analytics and direct marketing is preferred.
• Experience with one or more Advanced Data Science software languages (Python, R)
• Experience with structured or un-structured data analysis and tools (SQL, Spark, Tableau, Power BI tools)
• Experience with cloud-based platforms (AWS, Azure, Google)
• Demonstrated ability to communicate technical ideas and results to non-technical clients in written and verbal form.
• Strong organizational, management and leadership skills. Experience managing and mentoring junior resources across different geo-locations.
• Experience in industries such as hospitality, travel, retail, or other high volume consumer environments.
• Experience with personalization engines, recommendation systems, revenue/yield optimization, or demand forecasting.
• Familiarity with MLOps tools such as MLflow, SageMaker, Databricks Model Serving, or similar.
• Exposure to marketing tech or customer engagement platforms (e.g., Adobe Experience Cloud, Salesforce, Braze, Amperity).

Tech Stack

• AWS
• Azure
• Cloud
• Python
• Spark
• SQL
• Tableau

Benefits

• Recognition Programs and Rewards
• Excellent health care options, including medical, dental, and vision
• A people-first culture
• Go Hilton: Travel Discounts Program Hilton hotel rates worldwide.
• Perks at work: Employee Pricing platform
• Employee Assistance Program that supports your physical and mental well-being.
• Paid Vacation Time and Paid Sick Days
• 401(k) program with company match
• Tuition reimbursement programs
• Numerous learning and advancement opportunities
• And more!