The Data Science team at Penguin Random House is looking for a senior data scientist in a pricing focused role.
As a senior data scientist on the team, you will have the opportunity to advance a number of strategic projects under the umbrella of pricing, including measuring eBook pricing elasticity, improving audiobook pricing, sales forecasting, and bulk deal pricing recommendations, among others.
The ideal candidate brings a collaborative, R&D-oriented, and analytical mindset. The role emphasizes written communication and a continuous documentation of learnings, as well as the ability to convey complex technical results to a nontechnical audience.
While pricing remains the focus of your responsibilities, it also intersects with many other parts of the business. In addition to working closely with the data science team on these problems, you’ll need to collaborate with decision makers across the business to tackle industry-specific problems.
At Penguin Random House, you will:
• Take full ownership of the current infrastructure around algorithmic pricing
• Optimize and scale the business impact of existing automated pipelines, identifying efficiency gains and taking the initiative to improve them
• Oversee experiment design and the causal inference workstream, from early data exploration to analysis and delivering results
• Measure and evaluate event-driven sales from promotions, digital merchandising, market shocks, and yearly seasonality in order to inform pricing decisions
• Study additional interaction effects with respect to pricing, with the goal of turning research findings into actionable recommendations for stakeholders
• An undergraduate degree in statistics, economics, mathematics, computer science, industrial engineering, data science, or a social science with a quantitative focus
• 4+ years of professional experience programming in either R or Python (R preferred)
• Aptitude with shell scripting, debugging tools, containerized environments, and any flavor of Linux
• Experience executing and managing field experiments; familiarity with probability-based sampling designs
• Familiarity with automated feature engineering, data imputation, and working with large datasets
• A track record of applied Bayesian modeling/inference or machine learning techniques to real world data
• Ability to communicate complex technical concepts to a business audience
• Proficiency using Git version control software to contribute to a shared repository/codebase
• Data munging skills; experience working with relational databases and fluency in SQL
• A master’s degree or its foreign equivalent in a quantitative social science or related field. Alternately, two years of additional experience in a data science or ML role is a plus
• Familiarity with the R packages CausalImpact, ggplot2, lme4, rstanarm, LOO, and the tidyverse suite
• Expertise implementing models with Stan, WinBUGS, or other probabilistic programming framework
• Experience developing, testing, and deploying web applications using Shiny or RStudio Connect
• Experience building and maintaining R packages using packrat, Renv, and/or RSPM
• Expertise using cloud-based computing platforms and network analysis techniques
Full-time employees are eligible for our comprehensive benefits program. Please apply using our online application process, and please include your resume and cover letter.