Data Scientist I

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Full-time Regular Associate US

Who we are:

At Preferred Travel Group, we champion the power of travel to inspire meaningful connections and enrich lives around the world. As a global family of brands and programs representing the finest independent hotels and resorts, we are united by a shared belief in authenticity, collaboration, and the value of independent spirit. Our culture reflects our ideology in action: people first, relationships at the center, and a commitment to creating lasting impact for our partners, our global community, and one another.

When you join Preferred, you become part of a purpose-driven organization where ideas are welcomed, growth is encouraged, and your work contributes to shaping the future of travel.

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Why this role matters:

We are looking to hire an analytical, intellectually curious, business-minded, and results-driven Data Scientist who is passionate about using data to solve complex problems and uncover new opportunities. The Data Scientist is responsible for advanced analytical modeling, statistical analysis, and AI/ML-driven insights across PTG’s enterprise data platforms. This role partners closely with Data Engineering, BI Engineering, and business stakeholders to translate data into actionable intelligence, predictive models, and decision-support tools.

By uncovering patterns, forecasting outcomes, and transforming complex data into meaningful insights, this position helps drive smarter business decisions, identify growth opportunities, and create measurable value across the organization.

Success in this role comes from a focus on developing scalable models and analytical frameworks that improve operational efficiency, revenue performance, and strategic decision-making. Success also requires the ability to translate complex datasets into clear, actionable recommendations, deliver reliable and repeatable analytical solutions, and continuously identify opportunities where data science and AI can create meaningful business impact.

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What you’ll deliver:

• Data Science & Modeling
  • Develop, validate, and deploy statistical and machine learning models
  • Perform exploratory data analysis to identify trends, anomalies, and opportunities
  • Build predictive models (e.g., revenue forecasting, member retention, segmentation)
  • Design and evaluate experiments (A/B testing where applicable)
  • Develop feature engineering strategies across large datasets
• Business & Analytical Translation
  • Translate business requirements into analytical models and measurable outputs
  • Define key metrics, KPIs, and analytical frameworks with stakeholders
  • Provide data-driven recommendations to support strategic initiatives
  • Support financial, marketing, and operations teams with advanced analytics
• AI & Advanced Analytics
  • Support AI initiatives including recommendation models, automation, and agents
  • Apply advanced techniques such as:
    • Regression, classification, clustering
    • Time series forecasting
    • Natural language processing (where applicable)
  • Evaluate model performance and continuously optimize
• Work closely with Data Engineers to ensure data readiness and pipeline integrity
• Collaborate with BI Engineers to product ionize models into reporting layers
• Ensure models integrate into enterprise data architecture and workflows
• Partner with QA to validate data accuracy and model outputs
• Data Governance & Quality
  • Ensure data quality, consistency, and auditability of analytical outputs
  • Document methodologies, assumptions, and model logic clearly
  • Support compliance and audit requirements (SOC 2 alignment where applicable)

What you’ll bring to the team:

• Programming:
  • Python or R (required)
  • SQL (advanced)
  • Machine Learning / Statistical Modeling:
  • scikit-learn, Tensor Flow, PyTorch, or equivalent
• Data Platforms:
  • Experience working with data warehouses (Snowflake, Azure, etc.)
• Power BI, Tableau, or similar (for model output interpretation)
• Experience with:
  • Cloud platforms (Azure, AWS)
  • Hospitality, loyalty, or revenue…