Sr. Data Scientist 974 views

Vimeo’s platform provides the highest quality video tools for filmmakers, businesses, and video lovers around the globe. They take their insights seriously and encourages a culture of data-driven decisions for both product and business development. As members of the Business Intelligence team, they turn data into helpful, actionable insights for the entire organization and they are looking for an experienced senior data scientist to support their Business Intelligence and Data Analytics teams. This person should have a strong background in statistics and time series modeling and be an effective communicator with a wide variety of stakeholders. The ideal candidate is a self-starter with a bias for action and results, ideally with experience in a fast-paced, data-driven environment.

What you’ll do:

• Work alongside with their data analysts and provide mathematical and statistical guidance to ensure modeling best practices
• Develop and maintain general mathematical and statistical frameworks and models for use by data analysts
• Work alongside with their data analysts to design, implement, and run statistical experiments in partnership with Product Managers in the context of product development and optimization
• Develop, implement, and test time series (and other) models to detect trends and changes in trends to subscription, funnel, and financial metrics
• Create and maintain, in collaboration with their data engineers, high-quality aggregated data sets from unstructured raw data to efficiently address product and business questions
• Collaborate with Finance, Sales, Engineering, Marketing, and Product stakeholders to rationalize loosely defined questions and hypotheses into an automated and reusable analytical framework within the appropriate business context

Skills and knowledge you should possess:

• Master’s or Ph.D. with 2+ years in a Data Science role or Bachelor’s degree in a STEM field with 5+ years in a Data Science / Data Analytics role
• Experience with
  • SQL is a must
  • Python is a must with the usual data science-centric libraries
  • Working with large data sets (terabyte scale)
  • Working with Engineering teams is preferred
  • SaaS (specifically subscription) metrics and cohort modeling
  • Hypothesis testing, A/B testing, Bayesian inference, time series modeling, linear and non-linear regression, clustering and classification, as well as statistical and machine learning methods
• Strong analytical skills, data sensibility, and an inclination to educate
• Proven ability to manage multiple projects simultaneously and produce tangible results
• Can you explain Quadratic Discriminant Analysis to audiences of varying technical fluency?