Data Analytics Manager

4 weeks ago

Minneapolis, Minnesota, United States Capillary Technologies Full time
Job Summary

Capillary Technologies is seeking a highly skilled Data Analytics Manager to join our Consumer Insights Analytics team. As a key member of our team, you will be responsible for owning projects, providing actionable business insights, and communicating complex quantitative analysis to clients.

Key Responsibilities
  • Answer business questions by using appropriate methodology with available data.
  • Recommend analytic approaches to make data-driven decisions.
  • Interpret the results of analyses and communicate findings to internal and external stakeholders.
  • Recommend actions for the business based on findings from analytics.
  • Time management across requests to ensure on-time delivery.
  • Explore and evaluate available data for cleanliness and functional usage.
  • Collaborate within a cross-functional environment that includes internal stakeholders (Consumer Insights, Strategy, and Client Success functions) as well as external clients/stakeholders.
  • Develop 'best practices' for answering frequently raised business questions.

Requirements
  • 5+ years of work experience in an analytics role.
  • 5+ years of work experience with querying relational databases (e.g. SQL).
  • Competency manipulating and analyzing complex, high-volume, high-dimensionality data from varying data sources, including relational and unstructured data warehouses.
  • Aptitude to strike the right balance between quantitative methodology and providing timely answers to business questions.
  • Ability to communicate complex analytic results in an easily understood manner.
  • Ownership of projects and commitment to high-quality, on-time deliverables.

Preferred Qualifications
  • 2+ years of work experience with one or more analytical software platforms (e.g. SAS, SPSS, R or Python).
  • Work experience with business intelligence and visualization tools (e.g. Tableau, Power BI).
  • Degree in a relevant quantitative field (e.g. statistics, mathematics, economics, operations research or social sciences).

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