Senior Data Scientist

The Data Science program at GitLab focuses on developing model-based insights to help us understand our business, customers, and product better. Data Scientists work across the entire development lifecycle, from inception to final delivery. As a result of helping GitLab understand major trends across our business, Data Scientists make significant strategic contributions to new and existing business initiatives.

Data Scientists work with peers on the Data Team and functional teams to:

• perform ad-hoc exploratory analysis
• solve well-defined business problems
• regularly measure and improve analytics initiatives
• create and maintain production models and related applications

Example Data Science projects include:

• account scoring
• propensity to buy
• customer segmentation
• sentiment analysis
• customer churn and uplift prediction
• hypothesis testing and forecasting

Data Scientists are a part of the Data Team and report to the Director/ Sr. Director, Data & Analytics.

What you'll do in this role

The Senior Data Scientist has all of the responsibilities of an Intermediate Data Scientist, plus:

• Improve predictive models with data from multiple models
• Automate feedback loops for algorithms/models in production
• Create repeatable processes and scalable data products
• Influence functional teams and develop best practices across the organization
• Review, scale, and enhance operationalized statistical models and algorithms

We're looking for

The Senior Data Scientist meets all of the requirements of an Intermediate Data Scientist, plus:

• 6+ years professional experience in an analytics role
• 4+ years professional experience in a predictive analytics, data science, or similar role
• Developed 4 or more automated machine learning models for production use
• Developed and presented 6 or more predictive analytical projects
• Developed communication skills with ability to explain statistic and mathematical concepts to non-experts
• Extensive knowledge, application, and experience in creating and implementing recommendation systems, machine learning, NLP, statistics, and deep learning
• Ability to quantify improvements from business efficiency or customer experience based on research outcomes
• A shared interest in our values, and working in accordance with those values

Also, we know it’s tough, but please try to avoid the ​​confidence gap​.​​ You don’t have to match all the listed requirements exactly to be considered for this role.

Hiring Process

To view the full job description and hiring process, please view our​ ​handbook​. Additional details about our process can also be found on our ​hiring page​.

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