Senior Applied Scientist, Machine Learning

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.

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.

• 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 Git Hub 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

• 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

Competitive compensation, bonus structure, and comprehensive benefits. H1B transfer available if 3+ years remaining.

Our client is committed to diversity and inclusivity in the workplace.