Applied Machine Learning Scientist

Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom, and many other regions worldwide. In publishing the best books in every genre and subject for all ages, we are committed to quality, excellence in execution, and innovation throughout the entire publishing process: editorial, design, marketing, publicity, sales, production, and distribution. With the proliferation of data and the fast-changing dynamics within the publishing industry, data science and AI tools are vital to our business.

The Data Science team at Penguin Random House is seeking an Applied Machine Learning Scientist. We are an agile team of data scientists and software engineers. Data science at PRH truly runs the gamut, encompassing pricing systems, sales forecasting recommender/personalization systems, title segmentation, supply chain, ad-hoc analysis, and data exploration. The data science team is drawn from various disciplines and backgrounds; the group is well resourced and supported by data warehousing/engineering and DevOps functions.

Responsibilities:
In this role, you will own several high-priority projects/data products and be responsible for deliverables and relationships with other stakeholders in the business. This person will design and build ML models for demand forecasting at scale, and review models and code of other scientists. You will design experiments to validate scientific hypotheses and develop new techniques for inferring user interests from online/e-mail activities. In addition to working closely with the Data Science team on these areas, you'll need to collaborate regularly with decision-makers across the business to tackle industry-specific problems.

 Apply if you have:
* Degree in a quantitative discipline like Computer Science, Mathematics, Statistics, Operations Research, or relevant work experience
* Prior work experience in Ads ML, recommender systems preferred
* Intuition for mapping real word problems to relevant analytical methods, models, approaches
* Expertise in Python with and the ability to write performant production-quality code
* Solid capability in SQL for tasks such as computing aggregates and joining multiple tables


Preferred Qualifications:
* 2 years of professional experience in a data science role
* Familiarity (at least) with AWS and Kubernetes
* Familiarity (at least) with Docker and containerized workflows
* Experience building data products, from the warehouse ingestion phase, all the way through to the business-facing application side