Data Scientist- Customer Modeling

At Holiday Inn Club Vacations, we believe in strengthening families. And we look for people who exhibit the courage, caring and creativity to help us become the most loved brand in family travel. We’re committed to growing our people, memberships, resorts and guest love. That’s why we need individuals who are passionate in life and bring those qualities to work every day.

Do you instill confidence, trust and respect in those around you? Do you encourage success and build relationships? If so, we’re looking for you.

The Data Scientist, Customer Modeling is a core builder of our enterprise customer data and predictive analytics capability. This role transforms customer, behavioral, and performance data into predictive intelligence that drives activation, retention, optimized channel engagement, and long-term customer value.

Partnering closely with Performance Marketing, Analytics, Audience Strategy, and Technology, this role will lead the development of a suite of predictive and propensity models and ensures they are aligned to business priorities, validated in-market, and driving measurable ROI. The Data Scientist also provides leadership to an analyst who supports model development, validation, and exploratory analytics.

% of Time (equals 100%)

• Design, build, validate, deploy, and maintain a suite of propensity, attrition, LTV, and channel models that directly influence activation, retention, and ROI. (
  30%)
• Translate strategic business needs into modeling requirements
  • Lead partnership with cross‑functional stakeholders to define outcomes, prioritize development, and ensure models reflect business rules, funnel dynamics, and performance drivers. (20%)
• Support the assessment of data quality, understand transformations, define feature needs, partner with Technology identifying gaps in EDW, data capture, and documentation that impact modeling integrity. (25%)
• Establish rigorous measurement and testing frameworks
  • Including holdouts, back‑testing and lifecycle validation; continuously monitor model drift, re‑score, re‑train, and ensure KPIs (activation, usage, conversion, engagement, margin impact, etc) are accurately measured and communicated. (15%)
• Lead, mentor, and elevate analytical capability by overseeing an analyst supporting model development and validation, defining modeling best practices, and ensuring model outputs are understood, leveraged, and integrated into performance optimization across teams. (10%)

This job description in no way states or implies that these are the only duties to be performed by the employee in this position. It is not intended to give all details or a step‑by‑step account of the way each procedure or task is performed. The incumbent is expected to perform other duties necessary for the effective operation of the department.

Provides day‑to‑day leadership and oversight of 1‑2 analysts supporting modeling and validation efforts. Responsible for coaching, workload management, and establishing analytical standards for model development.

• BA/BS or MS in Data Science, Statistics, Computer Science, Applied Mathematics, or related quantitative field.
• 3–5+ years of hands‑on predictive modeling experience (marketing, CRM, or revenue optimization preferred).
• Demonstrated expertise in Python, R, Azure ML machine learning frameworks, and SQL.
• Experience working with large‑scale data environments, customer lifecycle data, and marketing/test design frameworks.
• Experience collaborating with Data Engineering and Technology teams to define data requirements and pipelines.

Valid driver’s license and reliable transportation (required). This role may include on‑site content capture at resorts and other properties.

• Deep knowledge of statistical modeling, machine learning algorithms, and feature engineering.
• Ability to translate complex analytical findings into clear, actionable insights for non‑technical leaders.
• Strong critical‑thinking and problem‑solving skills grounded in business outcomes and operational feasibility.
• Skilled in…