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Enabling collaboration for everyone through security, compliance and insight.

Data Scientist - Behavioral Analytics & Machine Learning

$80k – $100k • 0.1% – 0.4%
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We are looking for a talented theoretical and applied scientist to help build the next generation of our intelligent behavioral analytics platform for enterprise. This is a great opportunity for someone with deep expertise and interest in ML to make a large impact in the future of our platform. If you desire to work at the intersection of statistics, machine learning, and engineering to tackle some of the most challenging and interesting problems in the domain of enterprise social graph, we want to meet you!

Do you think about data science as a way to disrupt and reimagine how an enterprise operates? Is building enterprise-focused software with machine learning technologies and a hacker mentality intriguing to you? Now is your chance to work with our high energy, talented team in our fast-paced technical startup.

This position is full-time and based in our Columbus, OH office.


Responsibilities
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Develop, implement and continuously improve statistical and machine learning models.

Collaborate with Product and Engineering to solve problems and identify patterns/trends and opportunities.

Own the quantitative analysis process from idea to implementation.

Use data to challenge the status quo.

Develop new insights from within the enterprise social graph.

Produce models that analyze human behavior in a way which can predict future scenarios.


Minimum Qualifications
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MS/PhD in Mathematics, Statistics, Computer science, Physics or a related quantitative field. Advanced degrees preferred with 3 to 5 years working experience.

End-to-end experience in model development, validation, implementation, and feedback tracking.

Expert knowledge of machine learning and statistical modeling methods.

Expert in one of statistical packages such as R, MATLAB, SPSS, SAS, Stata, etc. and scripting language such as Python.

Ability to initiate and drive projects to completion with minimal guidance.

Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc.

Ability to communicate the results of deep analysis in a clear and effective manner.

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