Data Scientist III

Req #
Software Development

Overview & Responsibilities

Primary Responsibility:

Responsible for answering research questions and problem statements through the ongoing analysis and interpretation of data from various sources including ticketing, work tracking, web analytics, system monitoring, internal logging, and more. Using skills in modeling, simulation, and analysis, helps the business better understand its problem space by providing insights and recommendations for actionable optimizations. Presents findings and insights to business stakeholders and partners.


Job Complexity:

  • Works directly with stakeholders across product, business operations, engineering, and service delivery to understand and gather problem statements and research questions.
  • Helps design and implement systems that will collect or aggregate structured or unstructured data for later analysis.
  • Works with product and engineering to identify and define data gathering requirements for new initiatives/projects/applications/systems.
  • Leverages predictive modeling, machine learning, simulation, and other statistical and mathematical analysis techniques to solve or answer problem statements and research questions.
  • Presents analysis to business stakeholders, educating them about relevant technical details to enable understanding and drive informed decision-making.



Works under light supervision, will be expected to be self-directed. Should be able to plan and execute projects independently.



Minimum requirements:

  • Experience with R programming
  • Basic proficiency with at least one dynamic scripting language (JavaScript, Python, Ruby, Perl, etc).
  • Understanding and comfort with data extraction via API.
  • Experience using and comfort working in Github workflows.
  • Competence with database structures and design and some SQL development skills.
  • Intermediate Tableau, QV or other BI visualization tool skills including the ability to connect to data, build objects, and publish dashboards.
  • Ability to clearly communicate technical information and ideas so that non-technical audiences will understand.



  • Degree in a relevant discipline such as Finance, Computer Science, Mathematics, or Statistics.
  • Strong project management skills, with an ability to design, plan, and execute projects.
  • Experience with machine learning techniques, such as random forests, dimension reduction, etc.
  • Strong understanding probability, statistics, optimization, linear algebra, or related skills