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Job description
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 AI 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 GenAI 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 AI Enablement
Leverage tools such as GitHub Copilot, Claude, and similar assistants
Integrate GenAI 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 AI
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
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 comprehensivebenefits
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.