Sr Machine Learning Scientist

$150,000 - $200,000/Yr

Penguin Random House - New York, NY

Full-time - Mid Level

Remote - New York, NY

Educational Services

About the position

The Senior Machine Learning Scientist at Penguin Random House will lead the development of personalization products, focusing on recommender systems for various digital platforms. This role is pivotal in driving the company's digital transformation through advanced AI and machine learning techniques, enhancing customer engagement and book discovery.

Responsibilities

• Lead and own the design, development, and deployment of end-to-end machine learning projects for large-scale recommender systems and personalization products.
• Develop models that power real-time online marketing tools, including customer segmentation, ad targeting, and user engagement prediction.
• Design and run A/B tests to validate model performance, iterating based on experiment results and user feedback.
• Collaborate with cross-functional teams including engineering, marketing, and product to integrate ML solutions into business products.
• Stay up to date with industry trends and advancements in recommender systems, personalization, and AI-driven marketing technologies.

Requirements

• 5+ years of professional experience in machine learning, with a strong focus on recommender systems, personalization, and online marketing audience targeting models.
• Expertise in Python and key ML libraries (e.g., TensorFlow/PyTorch, NVTabular, Triton).
• Experience with cloud-based services (e.g., AWS, Kubernetes, Databricks), containerization (Docker), and deploying ML models at scale.
• Strong knowledge of SQL for querying and managing large datasets.
• Ability to communicate technical concepts and results effectively to non-technical stakeholders.

Nice-to-haves

• Master's or PhD in a quantitative discipline like Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience.
• Proven track record of building, deploying, and optimizing large-scale machine learning models in production environments.
• Experience in A/B testing, experimentation platforms, and online learning.
• Familiarity with MLOps tools and practices for managing the lifecycle of machine learning models in production.

Benefits

• Medical/Prescription drug insurance
• Dental insurance
• Vision insurance
• Health Care/Dependent Care Flexible Spending Account
• Health Savings Account
• Pre-Tax and Roth 401(k)
• Short and Long-Term Disability Insurance
• Life/AD&D Insurance
• Commuter Benefits
• Student Loan Repayment Program
• Educational Assistance
• Generous paid time off