Senior Applied Scientist, Machine Learning

About Our Client

Role Overview

Key Responsibilities

• Drive machine learning strategy across pricing, personalization, and recommendation systems
• Identify opportunities to maximize customer value through data-driven decisioning

• Design, build, and deploy ML models using behavioral and subscription data
• Develop systems for personalization, churn prediction, and conversion optimization

• Lead A/B and multivariate testing to evaluate model performance
• Optimize customer journeys, pricing strategies, and monetization levers

• Leverage tools such as GitHub Copilot, Claude, and similar assistants
• Integrate GenAI into workflows to accelerate model development and experimentation

• Apply deep learning, recommender systems, and representation learning
• (Nice to have) Implement reinforcement learning approaches such as contextual bandits, Q-learning, or Thompson sampling

• Partner with Product, Marketing, Engineering, and Sales teams
• Translate ML insights into measurable business impact

• Stay current with emerging ML techniques and industry trends
• Contribute to internal knowledge sharing and external thought leadership

Qualifications

• 8+ years in Applied Machine Learning or AI
• 3+ years in a technical leadership or mentorship capacity

• Personalization and recommendation systems
• Dynamic pricing or offer optimization
• Churn / propensity modeling for subscription products

• Strong background in classical ML and deep learning (e.g., XGBoost, Random Forest, neural networks)
• Experience with recommender systems and representation learning
• Proficiency in Python, SQL, and ML frameworks (e.g., PyTorch, Scikit-learn)

• Strong grounding in statistics, probability, linear algebra, and optimization

• Ability to clearly explain complex ML concepts to cross-functional stakeholders
• Proven ability to align technical solutions with business objectives

Work Environment

• Hybrid role based in Frisco, TX
• Candidates must be within commuting distance
• No relocation support available

Why Join

• Work on high-scale, real-world ML problems impacting millions of users
• Strong investment in AI/ML innovation and tooling (including GenAI)
• Collaborative, cross-functional environment with clear business impact
• Competitive compensation, bonus structure, and comprehensive benefits