Lead Machine Learning Scientist - Enterprise Products
San Francisco Bay Area, US - Internet
Lead Machine Learning Scientist - Enterprise Products
About the role
Linkedin is looking for an applied machine learning researcher to lead relevance optimization and data product development for its B2B products across Recruiting and Sales Solutions. You will play the role of an architect and shape the vision for relevance optimizations on critical business problems for LinkedIn's Enterprise suite of products. As a senior researcher, you will be working with a team of software and research engineers to help drive our next-gen machine learning technology initiatives for our fast-paced business products. This role is ideal for an individual looking to have a huge impact in transforming Enterprise Software Industry by unleashing the power of data to help drive critical business decisions.
Responsibilities
Develop machine learning models for next-gen Recruiting and Sales data products.
Perform studies to gain deeper Insights about how recruiting and sales industry is being transformed by Online networks and incorporate learnings into models.
Mentoring junior research engineers by providing guidance with regards to how they should go about applying advanced machine learning techniques to critical business problems.
Represent LinkedIn in academic and industry circles showcasing our innovation, data products and scientific expertise in bringing game-changing data products to market.
Required Skills
PhD in CS/Statistics/Maths/Physics from a top tier university
Strong command on programming and software engineering practices at a large scale internet company
Strong background on machine learning and data mining with a broad understanding of unsupervised and supervised learning methods. You will be expected to be proficient with methods such as Gradient Boosted Decision Trees, Matrix Factorization, Kernel Methods, LDA, or Multi-armed Bandits. You will also be expected to be familiar with newer approaches such as Deep Learning or Non-parametric Bayesian methods.
5+ years hands on experience working with large datasets (TBs) on Distributed Systems
Strong mathematical skills with knowledge of statistical methods.
Proven track record of publishing papers at top-tier Machine Learning/Data Mining/Theory conferences like KDD, WWW, WSDM, NIPS, RecSys, SIGIR, ICML etc.
No salary provided
Posted April 09, 2015 at 09:19PM from LinkedIn http://ift.tt/1aEtaxU
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