"Overview : This role is suited for a self-directed Senior Web Research Scientist to generate robust, actionable analytics from immense, real-world data sets.

Things you need to have: ​
Masters degree in Computer Science, Physics, Electrical Engineering, Statistics, or Mathematics, and 7+ years of related work experience OR a PhD and 5+ years of related work experience.

• Proficiency with C++ and a scripting language (Ruby, Python).
• Ability to develop system prototypes.
• Experience with statistical and mathematical libraries and software (R, Matlab, etc.)
• Excellent oral and written communication skills and a strong discipline for documenting methodologies and applications.
• Facility with standard machine learning techniques, error propagation, statistics, scientific thinking, and the ability to invent.
• A track record of thought leadership & contributions that have advanced the field

It would be great if you also had:

• Proficiency with relational databases and Linux.
• Experience working effectively with software engineering teams.
• Experience working with Internet data (corpus of HTML documents, browse clickstreams, server logs) Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Hadoop, Map-reduce)

What you will be doing:
We have been gathering and analyzing internet data for over 17 years, with terabytes upon terabytes of archived crawl data, millions of toolbar users in countries around the world,and 9 million unique website visitors each month. You will develop and apply rigorous mathematical and statistical models to semi-structured web data, formulate and test hypotheses, measure and propagate errors from data samples, and deliver web analytics and other data-derived services to be used by millions of digital marketers, web publishers, and investors worldwide. This position provides the qualified candidate with an opportunity to join our smart, motivated team and to directly impact our business.

Core responsibilities include:

• Develop novel statistical modeling techniques for pattern recognition problems.
• Develop or utilize code (Java, C++, or other object oriented language) for modeling (optimization, simulation, statistical).
• Build well-iterated models or analyses which reduce noise and maximize performance and accuracy.
• Contribute to strategic planning and project management for a variety of technical initiatives.
• Effectively communicate with senior management as well as with colleagues with computer science, technical research and business backgrounds.
• Document methodologies and increase our institutional knowledge based on experimental results and operationalized solutions

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