WHO WE ARE:

Xponential Fitness is the largest global franchisor of health and wellness brands. The portfolio of brands includes Club Pilates, the nation’s largest Pilates brand; CycleBar, the nation’s largest indoor cycling brand; StretchLab, a concept offering one-on-one and group stretching services; YogaSix, the largest franchised yoga brand; Pure Barre, a total body workout that uses the ballet barre to perform small isometric movements; Rumble, a boxing-inspired full-body workout; BFT, a functional training and strength-based fitness program; and Lindora, a metabolic health brand. Through the Company’s brands and the On-Demand virtual platform, XPLUS, Xponential Fitness continues to push their mission forward to make health and wellness accessible to everyone.

SUMMARY/OBJECTIVE:

The Principal Data Scientist will lead the development and deployment of AI/ML models that power strategic decision-making, automation, and innovation at Xponential Fitness. As a key leader within the Data, Analytics & AI pillar of the Technology department, this role is responsible for building scalable, high-impact AI-driven solutions that enhance customer engagement, operational efficiency, and predictive decision-making.
This role requires a strong blend of technical expertise, strategic vision, and business acumen to translate complex data science concepts into actionable business solutions. The Principal Data Scientist will collaborate closely with engineering, BI, and business teams while ensuring all AI/ML model development, deployment, and governance remain within the Technology department.
Pay Range: $175,000 - $190,000

QUALIFICATIONS:

• Experience: 10+ years in data science, machine learning, or AI-driven analytics, with at least 5 years in a senior or leadership role.
• Technical Proficiency: Expertise in Python, SQL, and Apache Spark for large-scale data processing, distributed computing, and production ML pipelines. Extensive experience with machine learning libraries such as Scikit-learn for traditional ML and TensorFlow/ PyTorch for deep learning, including model optimization and deployment at scale.
• AI/ML Model Deployment: Experience with MLOps, CI/CD pipelines, cloud-based AI architectures, and production model monitoring.
• Deep Learning & Advanced AI: Strong knowledge of NLP, computer vision, recommendation systems, and generative AI.
• Data Architecture & Engineering Collaboration: Familiarity with data pipelines, feature engineering, and enterprise-scale AI deployment.
• Business Acumen: Ability to translate AI capabilities into actionable business value while aligning with corporate goals.
• Communication & Influence: Ability to present AI insights to executive stakeholders and drive enterprise-wide adoption.
• Education: Ph.D. or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field.