Applied Data Scientist

Looking for a Data Scientist with a passion for experiments, anomaly detection, & ML models to better understand user behavior & preferences.

The Data Scientist will leverage telemetry and experimentation to build metrics and UX models; develop best in class monitoring and alerting methods to detect anomalies in product quality and partner with wide range of engineers and program managers to deliver solutions that help turn the overall business metrics. Ideal candidates should be able to identify a business or engineering problem and translate it to a data science problem, dig out sources of data, conduct the analysis that would reveal useful insights and also help engineering teams to operationalize the solution.

Responsibilities

* Identifies data sources, integrates multiple sources or types of data, and applies expertise within a data source in order to develop methods to compensate for limitations and extend the applicability of the data.

* Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis.

* Transforms formulated problems into implementation plans for experiments by applying (and creating when necessary) the appropriate methods, algorithms, and tools, and statistically validating the results against biases and errors.

* Interprets results and develops insights into formulated problems within the business/customer context and provides guidance on risks and limitations.

* Acquires and uses broad knowledge of innovative methods, algorithms, and tools from within our company and scientific literature, and applies his or her own analysis of scalability and applicability to the formulated problem.

* Validates, monitors, and drives continuous improvement to methods, and proposes enhancements to data sources that improve usability and results.

Qualifications

* Expert in one or more statistical software like R, SAS or Statistica etc.

* Expert in one or more scripting languages like Perl, Python or SQL

* Solid foundation of statistical modeling and machine learning algorithms and experimental design

* Deep understanding of big data systems including map reduce technologies like Hadoop and Spark

* B.S. and/or M.S. (Ph.D. Preferred) in Computer Science, Statistics, Operations Research or similar quantitative field

* 1 years plus experience of applying statistical modeling, ML and data mining algorithms to real world problems.

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