Data Analyst, Product

Remote Engineering

The Data Analyst, Product role at GitLab lives at the intersection of Product Analytics, Data Science, and Growth Marketing. This role reports into the Data Team and partners with the Growth section to support internal customers.  

The ideal candidate will have a strong analytical, product, and technical background in order to  proactively provide data-driven insights to define product vision, roadmap, and business strategy. Data Analyst, Product thrive at transforming data into convincing stories to influence their cross-functional partners to create the best customer experience and the best quality products.  

Responsibilities

  • Define and analyze metrics that monitor the health and success of products
  • Explore customer experience and product usage data to develop goals and metrics to ensure that product priorities are data-driven and aligned to both short-term and long-term company goals and OKRs. 
  • Create deep analytical insights around product use, performance, and customer experience by investigating funnels, user behaviors, short-term and long-term trends in product adoption. 
  • Identify opportunities for growth to remove obstacles in product adoption, retention, and engagement to accelerate the growth and market adoption of GitLab products 
  • Analyze results of experiments related to product adoption and growth to determine if a product feature should be launched 
  • Build strategic relationships with product stages to influence impact on products through data-driven recommendations and to ensure a shared vision for product improvement priorities. 
  • Expand our data warehouse with clean data, ready for analysis with a strong focus on data quality and data governance
  • Understand and document the full lifecycle of data from numerous sources and how to model it for easy analysis
  • This position reports to the Manager of Data 

Requirements

  • 2+ years of analytics experience, preferably in Product Analytics or Growth
  • Passionate about data, analytics, automation, data quality, and data governance 
  • Experience creating data models for large quantities of raw, disorganized data (we use dbt) and statistical models
  • Hands on experience with SQL (we use Snowflake), Python, Git, and GitLab 
  • Experience building visualizations in Business Intelligence tools (we use Sisense) and Product Analytics tools 
  • Strong systems background with an interest in connecting data across a variety of data sources. Our data includes Salesforce, Zuora, Zendesk, Marketo, NetSuite, Snowplow and many others.
  • Strong interpersonal, collaboration, and communication skills with a focus on results and efficiency
  • Share and work in accordance with our values
  • Successful completion of a background check

Hiring Process

Candidates for this position can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. To learn more about someone who may be conducting the interview, find her/his job title on our team page.

  • Selected candidates will be invited to fill out a short questionnaire.
  • Next, candidates will be invited to schedule a screening call with our Global Recruiters
  • Next, candidates will be invited to schedule a first interview with our Manager, Data (Analytics)
  • Next, candidates will be invited to schedule a second interview with our Director of Product, Growth 
  • Next, candidates will be invited to schedule a third interview with our Data Analyst
  • Next, candidates will be invited to schedule a fourth interview with the our Engineering Manager, Growth: Acquisition, Conversion, Telemetry or Manager, Data (Engineering) 

 

Compensation

To view the full job description and its compensation calculator, view our handbook. The compensation calculator can be found towards the bottom of the page.

 
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Gitlab

gitlab.com

From project planning and source code management to CI/CD and monitoring, GitLab is a single application for the entire DevOps lifecycle.


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