Data Scientist Responsibilities

Perform large-scale very-high-complexity data analysis and develop effective statistical models for segmentation, classification, optimization, and time series.
Understands technical architecture in depth, and influences improvements.
Design and implement reporting dashboards that track key business metrics and provide actionable insights.
Identify actionable insights, suggest recommendations, and consistently influences the overall data best practices (e.g.
analysis, goaling, experimentation) within the area and the direction of the business by effectively communicating results to cross-functional groups.
Work closely with Product or Engineering and Operations teams to proactively create rule and manage decisions.
Translates analytical understanding of the area to team priorities and strategic narrative.
Consistently drives top-line results with analysis, adapting strategy as needed.
Prioritize leads so that the teams can work on the most valuable cases.
Improves efficiency and simplicity of shared tools and libraries to help scale the team.
Demonstrates leadership in analytics org projects.

Minimum Qualifications

Requires a Master’s degree (or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Analytics, Statistics, Mathematics, Physics, or a related field
Requires a completion of a graduate-level course, research project, or internship in each of the following:
Performing quantitative analysis including data mining on highly complex data sets
Data querying language(s) including SQL
Scripting language(s) including Python
statistical or mathematical software including one of the following: R, SAS, or Matlab
Applied statistics or experimentation, such as A/B testing, in an industry setting
Machine learning techniques
Relational databases
Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics

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