Verified Remote Opportunities

About the company

Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. 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. Our vibrant and diverse international community of nearly 300 publishing brands and imprints include Ballantine Bantam Dell, Berkley, Clarkson Potter, Crown, DK, Doubleday, Dutton, Grosset & Dunlap, Little Golden Books, Knopf, Modern Library, Pantheon, Penguin Books, Penguin Press, Penguin Random House Audio, Penguin Young Readers, Portfolio, Puffin, Putnam, Random House, Random House Children's Books, Riverhead, Ten Speed Press, Viking, and Vintage, among others. More information can be found at http://www.penguinrandomhouse.com/.

Full job description

Penguin Random House is the largest trade publishing company in the world. The Data Science team is seeking an experienced Machine Learning Scientist to drive business-critical forecasting products.

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

This role may be filled at the Senior or Staff level depending on experience and interview performance. 

Location: Remote eligible (U.S.), but NYC area preferred.

Specific responsibilities include:  

• Own end-to-end ML systems: scoping, feature engineering, model development, backtesting/validation, deployment (with platform partners), monitoring/alerting, retraining cadence, and ongoing reliability improvements. 

• Create and maintain production-safe evaluation infrastructure: automated backtests, error decomposition, uncertainty quantification, data validation, regression gates, and auditable model/version lineage. 

• Build AI-assisted/agentic development workflows (e.g., Claude Code) to automate repetitive tasks with human review and measurable quality gates. 

• Define success metrics tied to business outcomes; communicate assumptions, limitations, and risk so model outputs are used correctly by stakeholders. 

• Write production-quality, testable code and support reproducible workflows. 

• Partner across functions to translate business needs into a prioritized technical roadmap and measurable impact. 

• Build and improve forecasts across time horizons and business segments (demand, inventory, supply chain, resource allocation), selecting approaches that balance accuracy, stability, interpretability, and operational cost. 

• Productize forecast outputs for stakeholders: clear definitions and assumptions, versioned releases, and reporting that explains what changed, why it changed, and how uncertainty should shape decisions. 

• Feature engineering, uncertainty quantification and calibration, hierarchical/segmented forecasting where appropriate. 

• Partner with operations, supply chain, inventory, finance, and marketing leaders. 

Qualifications and requirements

Please apply if you meet the following qualifications — Senior level:  

• 5+ years in applied ML/data science, including owning models in production (deployment, monitoring, incident response, retraining)

• Strong forecasting expertise (time-series methods, feature engineering, rigorous backtesting) OR deep expertise in Bayesian statistical methods and probabilistic programming

• Strong statistics fundamentals; comfort with probabilistic forecasting and explaining uncertainty in practical terms

• Strong Python (or R) and SQL; writes production-quality, testable code

• Strong communication and cross-functional collaboration with non-technical stakeholders

• Experience using AI-assisted development workflows responsibly (verification loops, reproducibility, automated checks)

Additional expectations — Staff level:  

• 8+ years in applied ML/data science, or PhD with 3+ years of applied experience

• Experience building ML systems end-to-end (not just models): backtesting frameworks, scheduled retraining, monitoring/alerting, and automated reporting into planning or decision workflows

• Demonstrated ability to inherit complex systems built by others and make sound architectural decisions with high autonomy

• Technical leadership: raises the bar on evaluation, reproducibility, and production practices; mentors less-senior team members

Additional information

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

The salary range for the Senior level is $180,000–$220,000. The salary range for the Staff level is $210,000–$250,000. All positions are currently eligible for an annual profit award or bonus, subject to company results.

Applications for this role will be accepted through September 6, 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 page.

Disclosure requirements pertaining to the collection of your personal data:

Responsible for processing the information provided in your application is the company specified in the job advertisement, with its registered office as indicated. The company processes your data for the purpose of establishing an employment relationship on the basis of Art. 6 (1) b GDPR / Section 26 (1) sentence 1 BDSG.

The retention period for your data is determined by the statutory time limits applicable in the respective country, beginning upon completion of the recruitment process. You can find these here.

You can contact the company’s Data Protection Officer at the above-mentioned postal address.

Further information on data protection and your rights can be found here.

We value the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, age, genetic information, or pregnancy.

All your information will be kept confidential according to EEO guidelines.

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Please apply if you meet the following qualifications — Senior level:  

• 5+ years in applied ML/data science, including owning models in production (deployment, monitoring, incident response, retraining)

• Strong forecasting expertise (time-series methods, feature engineering, rigorous backtesting) OR deep expertise in Bayesian statistical methods and probabilistic programming

• Strong statistics fundamentals; comfort with probabilistic forecasting and explaining uncertainty in practical terms

• Strong Python (or R) and SQL; writes production-quality, testable code

• Strong communication and cross-functional collaboration with non-technical stakeholders

• Experience using AI-assisted development workflows responsibly (verification loops, reproducibility, automated checks)

Additional expectations — Staff level:  

• 8+ years in applied ML/data science, or PhD with 3+ years of applied experience

• Experience building ML systems end-to-end (not just models): backtesting frameworks, scheduled retraining, monitoring/alerting, and automated reporting into planning or decision workflows

• Demonstrated ability to inherit complex systems built by others and make sound architectural decisions with high autonomy

• Technical leadership: raises the bar on evaluation, reproducibility, and production practices; mentors less-senior team members

Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. 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. Our vibrant and diverse international community of nearly 300 publishing brands and imprints include Ballantine Bantam Dell, Berkley, Clarkson Potter, Crown, DK, Doubleday, Dutton, Grosset & Dunlap, Little Golden Books, Knopf, Modern Library, Pantheon, Penguin Books, Penguin Press, Penguin Random House Audio, Penguin Young Readers, Portfolio, Puffin, Putnam, Random House, Random House Children's Books, Riverhead, Ten Speed Press, Viking, and Vintage, among others. More information can be found at http://www.penguinrandomhouse.com/.