About Our Client

Our client is a global technology company focused on consumer-facing digital products at massive scale. They leverage advanced machine learning and Â鶹´«Ã½Ó³»­ to deliver highly personalized user experiences, optimize monetization strategies, and improve customer outcomes across millions of users worldwide. The organization operates at the intersection of data science, product innovation, and real-time decisioning systems.


Role Overview

Our client is seeking a Senior Applied Scientist, Machine Learning to join their Consumer ML team. This is a hands-on, high-impact role focused on building and deploying machine learning solutions that drive personalization, pricing optimization, fraud detection, and customer journey improvements.


You will lead end-to-end model development, design experimentation frameworks, and leverage cutting-edge techniques including deep learning, recommender systems, and reinforcement learning. This role also emphasizes adoption of GenÂ鶹´«Ã½Ó³»­ tools to accelerate development and innovation.


Key Responsibilities


ML Strategy & Ownership

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

Model Development

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

Optimization & Experimentation

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

Generative Â鶹´«Ã½Ó³»­ Enablement

  • Leverage tools such as GitHub Copilot, Claude, and similar assistants
  • Integrate GenÂ鶹´«Ã½Ó³»­ into workflows to accelerate model development and experimentation

Advanced ML Techniques

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

Cross-Functional Collaboration

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

Research & Innovation

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


Qualifications


Experience

  • 8+ years in Applied Machine Learning or Â鶹´«Ã½Ó³»­
  • 3+ years in a technical leadership or mentorship capacity

Domain Expertise (Must Have at least one)

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

Technical Skills

  • 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)

Foundations

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

Communication

  • 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 or San Jose, CA
  • 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 Â鶹´«Ã½Ó³»­/ML innovation and tooling (including GenÂ鶹´«Ã½Ó³»­)
  • Collaborative, cross-functional environment with clear business impact
  • Competitive compensation, bonus structure, and comprehensive benefits