This a template job description. You can use this as a baseline for building out your RevOps team.
 

Data Scientist

Description

As part of the Insights team, this role requires the ability to gather and interpret data from disparate business data sources. You have the ability to manage and manipulate large amounts of data for the purposes of analysis and communication with the rest of the company. Your interpretation of the data will require a large amount of interaction with other teams to understand what the sources of data are, how this data might affect the business and its processes, and what problems are being solved by drawing conclusions from the data that has been collected. The interpretation of the data requires an understanding of the challenges facing the organization and must be clearly communicated so that concrete actions may be taken to tackle those challenges.

Responsibilities

  • You collect, manage, and maintain data stores for the company

  • You produce regular reports and analysis based on the data

  • You communicate findings and propose data-based projects or initiatives

  • You inform business processes and strategies based on data analysis and findings

  • You find out what challenges and pain points exist for each department and determine if those challenges can be investigated through the data science process

  • You provide insights into process that are not-obvious without rigorous data analysis

Experience

  • You are an experienced programmer and statistician

  • You are comfortable working in large, varying data sets and environments

  • You are able to adapt to different systems and gather data from those systems as needed

  • You have a strong understanding of RevOps processes and the challenges faced by RevOps organizations

  • You can translate sales and marketing requirements and challenges into actionable data projects

  • You have experience communicating technical information to non-technical or department specific audiences

Objectives / Outcomes / Measurement

An improvement in organizational productivity:

  • Increased understanding of underlying systems

  • Increased data processing efficiency and analysis

  • Increased cohesion of data across business sources

 

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You’ve learned that there are four areas of responsibility under RevOps: Operations, Enablement, Insights, and Tools.

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