Data Scientist

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., + 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: o Regression, classification, clustering o Time series forecasting o Natural language processing (where applicable)

• Evaluate model performance and continuously optimize
• Data Integration & Collaboration
• Work closely with Data Engineers to ensure data readiness and pipeline integrity
• Collaborate with BI Engineers to productionize 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, TensorFlow, PyTorch, or equivalent
• Data Platforms:
• Experience working with data warehouses (Snowflake, Azure, etc.)
• Visualization:
• Power BI, Tableau, or similar (for model output interpretation), With our in-office philosophy, our associates are expected to be in the office at least three days per week, supporting a healthy balance between in-person collaboration and flexible remote work. We take pride in our vibrant and inclusive culture, which thrives on meaningful connection, shared purpose, and cross-functional teamwork. In-office engagement plays a vital role in fostering spontaneous collaboration, accelerating innovation, and strengthening relationships across teams. It also provides valuable opportunities for mentorship, professional development, and a deeper sense of community.

Please note: While the current expectation is a minimum of three days per week in the office, this may evolve over time in alignment with business needs and our continued commitment to culture-building

• Experience with:
• Cloud platforms (Azure, AWS)
• Hospitality, loyalty, or revenue analytics (strong plus)
• Data marts / Kimball methodology environments
• Familiarity with:
• Feature stores, MLOps, model deployment pipelines
• AI-driven automation use cases, Having a bachelor’s or master’s degree in data science, mathematics, computer science or a related field along with 3-7 years of experience in data science or advanced analytics field plus experience working with large, complex datasets in production environments., * You thrive in an analytical environment where statistical thinking, experimentation, and evidence-based decision-making are highly valued.
• You are naturally curious and enjoy exploring data to uncover trends, patterns, and opportunities that others may miss.
• You enjoy translating complex data into meaningful stories and actionable insights that influence business strategy and outcomes.
• You balance independent problem-solving with strong collaboration, partnering across technical and business teams to deliver measurable impact.

Remote Hiring Remotely in United States 80K-100K Annually Mid level Remote Hiring Remotely in United States 80K-100K Annually Mid level Develop and deploy statistical and machine learning models, conduct exploratory analysis, forecasting, segmentation, experimentation, and AI initiatives. Translate business needs into analytical frameworks, KPIs, predictive insights, and recommendations. Collaborate with data engineering, BI, QA, and business teams to ensure data readiness, model integration, quality, governance, and auditability. Support revenue, marketing, financial, and operational decision-making through scalable analytical solutions. The summary above was generated by AI, $80,000 - $100,000, actual compensation within this range will be determined by multiple factors including candidate experience and expertise.

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.