Machine Learning Scientist, Personalization; Remote

Overview

Machine Learning Scientist, Personalization (Open to Remote)

The Data Science team at Penguin Random House is seeking a Machine Learning Scientist to help build and improve personalization products, including recommender systems for our websites, email programs, and online marketing initiatives.

We are investing in expanding our portfolio of business-critical personalization products and further improving our existing models. This role will own recommender models end-to-end, from model development and deployment to monitoring outputs, in close partnership with business stakeholders, platform engineers, and the rest of the personalization group.

We have a mature machine learning practice and strong infrastructure, supported by strong data warehouse and Dev Ops partners. We are transitioning to AI-accelerated development and use modern agentic coding tools (e.g., Claude Code) to speed up how we build and maintain forecasting systems, with rigorous quality gates including tests, reproducible workflows, and measurable improvements in model performance and reliability. Experience with Claude Code or agentic workflows is a plus, but we prioritize strong fundamentals and the ability and willingness to learn new workflows effectively.

• Build, evaluate, and iterate on recommender systems and personalization models that improve discovery across PRH’s digital channels.
• Develop models that support online marketing and engagement use cases, such as customer segmentation, propensity modeling, audience targeting, and engagement prediction.
• Define success metrics and use offline evaluation plus online experimentation (including A/B tests) to validate performance, monitor quality over time, and drive ongoing iteration.
• Partner with engineering and platform counterparts to product ionize models, including repeatable training, deployment workflows, monitoring, and refresh strategies.
• Diagnose model performance issues and data quality problems; communicate findings and recommended actions clearly to stakeholders.
• Write maintainable, production-minded code and contribute to team standards (code review, documentation, reproducibility, and testing where appropriate).
• Stay current with advances in recommender systems and applied AI, and bring practical ideas back to the team.

• Masters with 2+ years of applied work experience OR PhD in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or a related quantitative field
• Strong proficiency in Python and common ML frameworks and libraries (for example PyTorch or Tensor Flow)
• Strong SQL skills and experience working with large datasets for feature development, analysis, and validation
• Experience taking models from development to production (batch scoring, APIs, or downstream integration)
• Solid understanding of experimentation and measurement
• Becutting edge. Use the latest AI tools to develop well-designed and robust software
• Strong communication skills and ability to translate between business goals and technical solutions

• Experience with recommender systems, personalization, ranking/retrieval, or marketing targeting models
• Familiarity with cloud and modern data/ML tooling (AWS, Databricks, Docker, Kubernetes, Spark, or similar)
• Exposure to MLOps concepts and tooling (model registries, pipelines, monitoring, reproducibility)
• Experience with real-time or near real-time prediction systems

Please be advised that candidates selected to advance to the 1st round of interviews will be required to show photo  camera, and final interviews for this role will be in person at a Penguin Random House location.

The salary range for this position is $130,000 - $175,000. All positions are currently eligible for an annual profit award or bonus, subject to company results.

Applications for this role will be accepted through March 25, 2026 or until the role is filled. We encourage you to apply early, as we review applications on a rolling basis. Please include your resume and cover letter for consideration. Before applying for any role at Penguin Random House, we recommend you review our applicant resources page and our FAQs…