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Staff/Senior Machine Learning Scientist - Pricing/Forecasting (Open to Remote)
- New York, New York, United States
- New York, New York, United States
Über
Penguin Random House is the largest trade publishing company in the world. The Data Science team is seeking two experienced Machine Learning Scientists to drive business‑critical forecasting and pricing products — one focused on demand forecasting and one focused on e‑book pricing optimization.
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.
Both roles 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 (both roles)
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.
Forecasting role – additional responsibilities
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.
Pricing role – additional responsibilities
Full technical ownership of our automated e‑book pricing system, including model architecture (Bayesian hierarchical models), inference pipelines, and decision logic.
Design, run, and analyze backtests and live A/B tests to validate pricing strategies and measure real‑world revenue impact.
Evaluate when to enhance the existing system versus migrate to new approaches; make and execute on architectural recommendations.
Balance revenue optimization with brand considerations and sales stability.
Collaborate with the print book pricing team, identifying transferable techniques and shared infrastructure.
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 Ph.D. 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: raise the bar on evaluation, reproducibility, and production practices; mentor 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.
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 June 27, 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.
Benefits Full‑time employees are eligible for our comprehensive benefits program. Our range of benefits includes, but is not limited to, medical/prescription drug insurance, dental, vision, 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 and generous paid time off.
Penguin Random House values the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status.
Company: Penguin Random House LLC | Job ID: 289320
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Sprachkenntnisse
- English
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