Senior Decision Scientist Discovery & Intelligence

Simon & Schuster is a global leader in general interest publishing, dedicated to providing the best in fiction and nonfiction for readers of all ages, and in all printed, digital, and audio formats. Its distinguished roster of authors includes many of the world’s most popular and widely recognized writers, and winners of the most prestigious literary honors and awards. It is home to numerous well-known imprints and divisions such as Simon & Schuster, Scribner, Atria Books, Gallery Books, Pocket Books, Adams Media, Simon & Schuster Children’s Publishing and Simon & Schuster Audio and international companies in Australia, Canada, India, and the United Kingdom, and proudly brings the works of its authors to readers in more than 200 countries and territories. For more information visit our website at www.simonandschuster.com.

The Role

Simon & Schuster is investing in Data & Decision Intelligence to embed data, tools, and automation into everyday work and enable faster, better-informed decisions. The Senior Decision Scientist, Discovery & Intelligence will lead the development of AI-enabled discovery, ranking, and recommendation capabilities that turn complex content and market information into actionable intelligence. This senior individual contributor will set technical direction, own production outcomes, and raise the quality and speed of the decision-science practice.

What You Will Do

• Lead discovery science. Define modeling approaches, evaluation standards, and reusable patterns for retrieval, ranking, recommendations, similarity, classification, and content understanding.
• Build advanced models. Develop multi-stage retrieval and ranking systems using NLP, embeddings, semantic methods, entity resolution, graph techniques, and machine learning.
• Design credible evaluation. Combine offline metrics, human judgment, experiments, and business outcomes to measure relevance, coverage, diversity, bias, explainability, and value.
• Use AI to improve speed to market. Apply approved generative AI and AI-assisted development across research, coding, feature development, evaluation, testing, and prototyping while establishing rigorous validation and human-review controls.
• Own the solution lifecycle. Build, package, deploy, monitor, and maintain models and AI-enabled workflows; implement testing, versioning, performance and drift monitoring, and refresh processes.
• Create reusable intelligence products. Work directly with business stakeholders and partner with Analytics Engineering, Data Platform & Engineering, and forecasting teams to establish governed inputs, scalable services, feedback loops, support models, and responsible downstream use.
• Lead through influence. Translate complex methods clearly, mentor colleagues, guide technical tradeoffs, and promote reproducible, responsible data science and AI.

What You Bring

• Relevant experience. 6+ years in data science, machine learning, applied research, or a related role, including leadership of complex analytical products.
• Deep discovery expertise. Advanced Python and SQL with strong experience in search, ranking, recommendations, NLP, embeddings, similarity, entity resolution, or graph-based methods.
• Production capability. Experience moving models from experimentation into reliable production services or workflows using modular code, APIs or batch processing, automated tests, Git, CI/CD, monitoring, and cloud deployment.
• Practical AI leadership. Demonstrated use and evaluation of generative AI, foundation models, or AI-assisted development with appropriate privacy, bias, explainability, and human-oversight controls.
• Senior partnership. Ability to frame ambiguous problems, communicate uncertainty and tradeoffs, influence technical and business leaders, and mentor decision scientists.

Preferred

• Advanced discovery systems. Experience with vector databases, RAG, multimodal models, large-scale recommenders, learning-to-rank, knowledge graphs, or weak supervision.
• Experimentation. Experience designing online or quasi-experiments, human-evaluation programs, and feedback-driven model improvement.
• Industry background. Publishing, media, retail, marketplaces, or consumer-products experience; advanced quantitative degree or equivalent experience.

An Inclusive Workplace. We welcome candidates with different paths and perspectives. If you do not meet every preferred qualification, we still encourage you to apply.