(Senior) Data Scientist vacancy at GitLab
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:
propensity to buy
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:
Communicate with business partners to understand their needs to help develop new strategic insights
Define, collaborate, and communicate key influences, levers, and impacts to non-technical audiences
Perform exploratory data analysis to understand ecosystems, behavioral trends, and long-term trends
Build machine learning models (training, validation, and testing) with appropriate solutions for data reduction, sampling, feature selection, and feature engineering
Design and evaluate experiments (including hypothesis testing) by creating key data sets
Apply data mining or NLP techniques to cleanse and prepare large data sets
Help grow the Data Science function by defining and socializing best practices, particularly within a DataOps and MLOps data ecosystem
Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these standards through code review
Document every action in either issue/MR templates, the handbook, or READMEs so your learnings turn into repeatable actions and then into automation following the GitLab tradition of handbook first!
Ability to use GitLab
4+ years professional experience in an analytics role
2+ years professional experience in a predictive analytics, data science, or similar role
Developed 2 or more automated machine learning models for production use
Developed and presented 4 or more predictive analytical projects
Familiarity with the CRISP-DM analytics development model
Experience working with a variety of statistical and machine learning methods (time series analysis, regression, classification, clustering, survival analysis, etc)
Professional experience with python, including python data libraries (numpy, pandas, matplotlib, scikit-learn), or R
Deep understanding of SQL in data warehouses (we use Snowflake SQL) and in business intelligence tools (we use Sisense for Cloud Data Teams)
Working knowledge of statistics
Comfort working in a highly agile, intensely iterative environment
Positive and solution-oriented mindset
Effective communication skills: Regularly achieve consensus with peers, and clear status updates
Experience owning a project from concept to production, including proposal, discussion, and final delivery
Self-motivated and self-managing, with excellent organizational skills
Share our values, and work in accordance with those values
Ability to thrive in a fully remote organization
Successful completion of a background check
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.
How to apply?
To view the full job deion and hiring process, please view our handbook. Additional details about our process can also be found on our hiring page.
Before you apply, please check if any restrictions apply in terms of time zone or country.
This job has a geo-restriction in place: Anywhere.