Data Science Jobs in United States
There are 4,559 open Data Science jobs in United States on freehire right now. 1,063 of them were posted recently. The skills employers ask for most often are data-science, machine-learning and python.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| USD | year | $154,450 | $184,750 | $217,312 | 912 |
| USD | hour | $30 | $33 | $48 | 28 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- data-science 71%
- machine-learning 65%
- python 64%
- analytics 58%
- ai 55%
- sql 50%
- statistics 46%
- cloud 30%
How the work is done
- Remote 722 · 16%
- Hybrid 638 · 14%
- Onsite 237 · 5%
Visa sponsorship offered in 45% of the 898 postings that state a position on it.
Seniority
- Senior 1,265
- Lead 272
- Staff 262
- Principal 245
- Intern 119
- Middle 85
Who is hiring
- 1000+ employees 1,157
- 501-1000 employees 333
- 51-200 employees 88
- 11-50 employees 47
- 201-500 employees 15
- 1-10 employees 3
Data Scientist - consultant
Design and implement AI/ML models for product development, intelligent search, content enrichment, and metadata generation in a cross-functional team.
Senior Applied AI Engineer – Data Science & Analytics with Security Clearance
Build AI-powered data science and analytics tools for a government cybersecurity mission, requiring an active Top Secret clearance with polygraph.
Pega Data Science and Analytics
Build and maintain Pega-based data science pipelines and analytics scripts to replicate customer data in external systems like Databricks, enabling deeper analysis and standardized reporting for the team.
Data Scientist I
Data Scientist at Esri builds and deploys ML models for customers using Python and spatial analytics, collaborating with GIS teams to solve business problems in industries like defense, utilities, and transportation.
Data Scientist
Build predictive models and ETL pipelines for marketing analytics, using Python, SQL, and cloud tools to deliver client insights and segmentation.
Senior Data Scientist
Design, develop, and deploy AI/ML models using S&T data to support data-driven portfolio decisions for the ONR Comptroller.
Principal Data Scientist
Lead advanced healthcare analytics, AI/ML modeling, and thought leadership to develop data-driven solutions and patents from complex datasets.
Data Scientist
Senior Data Scientist builds and implements AI, ML, and statistical models to solve complex healthcare data problems, ensuring consistency and quality across the organization.
Data Scientist
Build and deploy ML models for commercial banking pricing, profitability, and deal insights using Python, SQL, and LLMs, then ship them to production.
Senior Data Scientist
Build and deploy data models to extract insights from private-market investment documents using SQL, Python, and AI tools, then visualize findings for institutional clients.
Data Scientist
Builds reproducible data workflows and interactive dashboards in R, Python and SQL to analyze population health metrics and inform public-health decisions.
Data Scientist
Build and deploy ML models to analyze retinal imaging data, helping diagnose and manage eye diseases like diabetic retinopathy and AMD.
Data Scientist
Build and deploy ML models to detect fraud and optimize dispute processes using Python, SQL, and Tableau for PayPal’s global payments platform.
Data Scientist
Build and deploy ML models to analyze credit exposure, optimize risk strategies, and extract insights for PayPal’s SMB payments business using Python, SQL, and cloud platforms.
Data Scientist
Build and deploy fraud-risk models and dashboards to protect PayPal’s global payments network, using Python, SQL, Tableau, and machine-learning techniques.
Data Scientist
Build and deploy real-time fraud-detection models for PayPal’s global payments platform using Python, SQL, and ML frameworks to analyze transaction data and reduce losses.
Sr Data Scientist, Risk Strategy
Build and deploy ML models to detect fraud and analyze risk in crypto trading, using graph analytics and unsupervised techniques while collaborating with engineering and product teams.