below marketmost similar roles pay hereabove market
This role pays less than
73%
of similar roles. Most pay
$126,800–$185,500
— the blue band above.
At the midpoint, this role pays about
$131k
versus about
$156k
for comparable roles.
Based on 240 similar postings.
Employer
About GitLab
GitLab is an all-remote software company that develops an AI-powered DevSecOps platform combining source code management, CI/CD, security scanning, and project planning in a single application.
GitLab currently has
48 open roles
on FindRole.
Listed pay typically runs
$152,800–$248,600
across 42 roles with salary data.
As a Data Scientist, Enterprise Analytics, you will join the Enterprise Analytics team to serve as a strategic analytical partner for Sales, Revenue Operations, and Finance. You will perform exploratory data analysis to uncover behavioral trends and build productionized machine learning models for propensity, churn, and expansion. Your daily work involves designing growth experiments, building agentic workflows, and contributing to the Semantic Layer to support company-level reporting on metrics like ARR and consumption. You will utilize Python, SQL, pandas, NumPy, scikit-learn, LightGBM, and XGBoost within cloud data warehouses like Snowflake. Key responsibilities include applying statistical methods, causal inference, and MLOps practices to solve complex go-to-market problems, ensuring that technical insights regarding activation, conversion, and retention are communicated clearly to non-technical stakeholders.
What does a Data Scientist earn in Remote?
Median $211278 from 36 postings across 19 companies.
Perform exploratory data analysis to identify behavioral trends and key drivers of business performance.
Build and productionize machine learning models for propensity, lead scoring, churn, and expansion.
Design, run, and evaluate growth experiments including A/B tests and quasi-experiments on pricing and onboarding.
Build and operationalize agentic workflows for analysis, modeling, and automated pipeline tasks.
Contribute to the Semantic Layer to enable stakeholders to self-serve metrics from trusted sources.
Write production-grade Python and SQL to maintain high-scale database performance and internal coding standards.
Communicate technical insights and strategic recommendations clearly to non-technical business stakeholders.
What we're looking for
3-5 years of professional experience in GTM analytics, data science, or a similar technical role.
Demonstrated ability to translate ambiguous business problems into measurable questions and communicate technical concepts to non-technical stakeholders.
Experience with experimentation and causal inference, including A/B testing, power analysis, and quasi-experimental methods.
Experience with statistical and machine learning methods such as regression, classification, clustering, and survival analysis.
Deep, hands-on understanding of SQL in cloud data warehouses and business intelligence tools like Looker, Tableau, or Hex.
Experience using Python for statistical modeling and machine learning using libraries such as pandas, NumPy, scikit-learn, LightGBM, and XGBoost.
Hands-on experience building agentic workflows with AI coding agents and connecting them to platforms such as MLflow.
Experience working in a B2C company with motions and metrics including Consumption, CRR, ARR, and Churn & Contraction.
Python
SQL
Data Engineering
Data Science
Machine Learning
Data Pipelines
GitHub
Databricks
ML Flow
dbt
KNime
Spotfire
PowerBI
SIMCA
JMP
AVEVA PI
LIMS
ELN
MES
ERP
GxP
Python
PySpark
Palantir Foundry
Machine Learning
Artificial Intelligence
Data Mining
Data Visualization
Data Analysis
Distributed Data Pipelines
Structured Data
Unstructured Data
IoT
Python
R
SQL
Machine Learning
Natural Language Processing
Azure
AWS
Google Cloud Platform
Azure Data Factory
Azure Functions
Azure Storage
Data Pipelines
DevOps
DataOps
Agile
Data Visualization
Data Mining
Data Governance