Efficient Frontier is a leader in online digital marketing, managing search marketing, display and social media campaigns for advertisers and agencies around the world. Efficient Frontier currently manages more than $1 billion in annual digital marketing spend on behalf of its clients globally.

In May 2011, Efficient Frontier acquired Context Optional, the leading provider of social marketing management solutions for global brands on the leading social networks, including Facebook and Twitter. Context Optional’s Social Marketing Suite enables global enterprises to build, manage and measure their brand presence, and engage their fans to increase mindshare, word of mouth, customer loyalty and website traffic. Together, Efficient Frontier and Context Optional offer a complete solution for brands to acquire, activate and drive value from fans on Facebook and Twitter.

Efficient Frontier is headquartered in Sunnyvale, California, with offices in New York, Chicago, the United Kingdom, France, Germany, and India, and technology licensing partnerships in Japan, Hong Kong and Australia. Context Optional is headquartered in San Francisco. Efficient Frontier is a privately held company with funding from Redpoint Ventures and Cambrian Ventures. For more information on Efficient Frontier, visit http://www.efrontier.com and for Context Optional visit http://www.contextoptional.com.

Efficient Frontier is looking for Senior Statistician with knowledge of statistical modeling concepts to develop and deploy large-scale online ad targeting systems.

Principal Responsibilities and Duties

Implement ad targeting models that use advanced statistical and machine learning techniques

The ideal candidate would research techniques in academia/ industry and develop new methods for Efficient Frontier's clients

Develop and implement algorithms that work with large scale data to forecast and optimize return on online advertising spend that Efficient Frontier manages

Build and deploy real-time online ad bidding system that leverages these models and algorithms

Collaborate with product management and engineering groups for new product features/ enhancements

Requirements

MS/PhD in Computer Science, Statistics or related fields is required. Recent Ph.D. graduates or Ph.D. candidates are strongly encouraged to apply

Command of C/C++, Python, R and Unix/Linux

Must have solid understanding of statistical modeling/machine learning/ data mining/ recommender systems concepts

Demonstrated ability to deal with very large datasets

Strong analytical quantitative and problem solving ability

Experience with architecting, building and deploying reliable algorithms-based ad optimization systems that work at scale is a plus.

A solid understanding of Hadoop, Hive and Map/Reduce programming is desirable

Knowledge of databases & their structure (Oracle, Postgres, MySQL)

Excellent communication and relationship skills & a strong team player

Efficient Frontier is an Equal Opportunity Employer