Senior Machine Learning Scientist (Open to Remote)
Penguin Random House, New York, NY
Home of the world’s best books.
The immediate remit for this role will be around demand forecasting, which is a well-defined business case with a clear, clean – and, in at least a couple of obvious ways, improvable – performance benchmark established by Amazon. The ideal candidate will have experience with and active interest in deep-learning-based, probabilistic time series models.
PRH is a private company with a deliberate, long-horizoned approach to innovation and you’ll be working alongside best-in-industry DevOps and Data Engineering teams. The company pays competitively and has consistently rated in the top 3 in Forbes “Best Places to Work” among mid-sized companies. Your colleagues will be engaged with, curious about, and motivated by their work but also value work-life balance and outside-of-work experiences. If this culture sounds appealing then it will be a good fit.
**The team is open to considering candidates from a senior individual contributor through to manager level candidates who have led small teams**
* Build machine learning models for business cases in demand forecasting, supply chain management, marketing, sales, and ecommerce/personalization
* Develop new algorithms, features and techniques building upon the latest results from the academic research community
* Propose and validate hypotheses to direct our business road map
* Focus on identifying and solving stakeholder problems with simple and elegant solutions
* Design, develop, and implement production level code. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment.
* Take ownership. Understand the needs of various teams, distill those into coherent projects, and implement them with an eye on long-term impact.
* Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects.
* Be ambitious. Find and eagerly tackle hard problems.
* Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to resources and will need to learn how to use them effectively.
* Masters with 8+ years OR PhD with 3+ years of applied work experience in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or a related quantitative field
* Proficiency in algorithm and model development, model validation and model implementation for large-scale applications in online commercial settings
* Experience distilling stakeholder requirements into problem definitions, dealing with ambiguity and competing objectives
* Ability to apply theoretical models in an applied environment
* Strong fundamentals on a broad set of ML approaches and techniques
* Strong fundamentals in problem solving and algorithm design
* Peer reviewed scientific contributions in relevant field
* Strong interest in learning, researching, and creating new technologies with commercial impact
* Experience with in deep-learning-based, probabilistic time series models
The salary range for this position is $120,000-$250,000, based on PHD completion, strong engineering background, and several years of experience and a track record of making a strong impact in commercial environments. Full-time employees are eligible for our comprehensive benefits program. Please apply using our online application process, and please include your resume with salary requirements.
About Penguin Random House
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.
Want to learn more about Penguin Random House? Visit Penguin Random House's website.
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