Data Scientist Salary Overview
Data Scientists at SaaS companies build machine learning models, design experiments, and generate deep analytical insights that shape product strategy and business outcomes. They work closely with Data Analysts on data pipelines and metrics, Software Engineers on model deployment, and Product Managers on feature experimentation. They typically report to an Engineering Manager or Director of Engineering.
Data Scientist compensation reflects the premium placed on ML and AI skills across the SaaS industry. The role commands some of the highest individual contributor salaries, with career progression into senior research roles, ML engineering leadership, or staff-level positions. View all SaaS salary benchmarks.
Detailed Data Scientist Compensation Breakdown
Percentile Band | Average Base Salary | # of salaries |
|---|---|---|
| Top 25% | $170,744 | 21 salaries |
| Middle 50% | $95,428 | 42 salaries |
| Bottom 25% | $49,239 | 14 salaries |
What Drives Higher Data Scientist Pay?
ML/AI expertise — deep learning, NLP, and recommendation systems command premiums
Python and R proficiency with production-grade code quality
Experimentation rigor — A/B testing frameworks, causal inference, Bayesian methods
Production ML experience — deploying and monitoring models at scale
Data Scientist Compensation Structure
Base salary is 80–90% of total cash compensation
Equity is significant at AI-focused companies (0.05–0.30%)
Performance bonuses tied to model impact and business outcomes (10–20%)
Research grants, conference stipends, and education budgets common at top firms
