At Cypress, we’re on a mission to build an essential testing platform that makes automated testing delightful and effective. Cypress provides better, faster, and more reliable testing for anything that runs in a browser. Hundreds of thousands of developers and QA professionals use Cypress.io to write better code faster and release with confidence.

Cypress is currently used in over 90 countries by hundreds of thousands of developers across more than 30,000 organizations. Cypress has over 1,800 customers in more than 58 countries across 45 industries and includes marquee names like Atlassian, Crunchbase, GitHub, PayPal, and Slack.

The company was founded in 2015 and has raised $55M in capital to date, including a $40M Series B financing in November 2020, led by OpenView Partners, with participation from Bessemer Venture Partners, Battery Ventures, Sapphire Ventures and Stripes.co. 

The goal of the Data Science and Analytics Team is to generate actionable insights and data-powered products for both the Cypress team and our customers.

We’re looking for a Data Scientist who can work on a diverse set of problems like determining the core metrics and targets for our products and services, building predictive models for estimating usage, conducting statistical experiments for optimizing engagement, and analyzing product adoption & user behavior. If you are excited about deriving insights from data and motivated by having an impact on the business, we want to hear from you.

You will:

  • Work closely with product and go-to-market teams to develop the data science roadmap, identify important questions and answer them with data
  • Apply statistical and econometric models on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict future performance of users or products
  • Design, build, document and maintain data models to support point-and-click analytics and visualizations as well as machine learning models
  • Push data and insights about products and customers to customer facing teams through their operational tools
  • Design, analyze, interpret, and communicate the results of statistical experiments
  • Drive the collection of new data and the refinement of existing data sources
  • Partner with product managers, engineers, operations and leadership to translate data insights into decisions and action

Requirements

  • 3-5 years of experience working with and analyzing data to solve problems
  • An MS or PhD in an quantitative field of study (e.g., Economics, Statistics, Sciences, Engineering, CS)
  • Expert knowledge of Python and its various machine learning frameworks and data processing tools
  • Extensive experience with SQL (dbt experience a plus)
  • Familiarity with BI platforms, such as Looker (preferred) or Mode
  • Experience deploying models in a production environment
  • Strong knowledge of statistics and experimental design
  • Demonstrated track record of identifying, scoping and leading complex data science projects with cross-functional partners
  • The ability to communicate results clearly and a focus on driving impact
  • Deep understanding of SaaS company metrics, particularly in the context of product-led growth

We are an inclusive employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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