Data Scientist Jobs
Data Scientists combine statistical analysis, machine learning, and domain expertise to extract insights from complex datasets. These roles span industries from tech to healthcare, finance, and beyond.
Last updated: August 17, 2026
Latest Data Science Jobs
View all jobsDATA SCIENTIST / MACHINE LEARNING OPS – EXPERT GCP (H/F)
Stage - Data Scientist / Machine Learning Engineer (f/m/d)
Data Scientist-Python & Gen AI
AI ENGINEER - DATA SCIENTIST
S&C Global Network - AI - Retail - Consultant - Retail Specialized Data Scientist
Medior Data Scientist / ML Engineer
Consultant(e) Data Scientist / AI Engineer
Senior Lead Analyst - Data Science - Machine Learning & Gen AI - UK
AI-First Data Scientist
Data Scientist, Data Scientist Internship, AI Engineer, AI Engineer Internship
Junior Applied AI & Data Scientist
Senior AI Data Scientist
AI/ML Engineer
AI ENGINEER - DATA SCIENTIST
Data Scientist (Recommendation)
Data Scientist - Python/SAS/SQL & AI/ML Solutions
Senior Data Scientist - AI Governance
Senior AI Data Scientist
Data Scientist - QuantumBlack, AI by McKinsey
Data Scientist, YouTube, ML Classifiers
Frequently Asked Questions
What is the difference between a Data Scientist and an ML Engineer?
Data Scientists focus on analysis, experimentation, and building models to answer business questions, while ML Engineers focus on taking those models to production with scalable infrastructure and pipelines. Data Scientists typically earn an average of $117K with a range of $95K-$145K, compared to ML Engineers who average $125K-$160K. The Data Scientist role is projected to grow 34% from 2024-2034 according to the Bureau of Labor Statistics, making it one of the fastest-growing occupations in the country. Both roles require strong Python skills, but Data Scientists lean more heavily on statistical analysis and experimentation.
What tools do Data Scientists use?
The core Data Scientist toolkit includes Python, R, SQL, Jupyter notebooks, pandas, and scikit-learn for analysis and modeling. For big data workloads, tools like Apache Spark are essential for processing datasets that don't fit in memory. Visualization libraries such as matplotlib and Plotly help communicate findings to stakeholders. Cloud platforms (AWS, GCP, Azure) are increasingly required as companies move data infrastructure to the cloud, and familiarity with version control and collaborative notebooks is now a baseline expectation.
Is data science still a good career in 2026?
Data science remains an excellent career choice in 2026, with the Bureau of Labor Statistics projecting 34% job growth from 2024-2034, far outpacing the average for all occupations. The average Data Scientist salary of $117K provides strong earning potential even at the mid-level, with senior roles pushing well above $145K. While the field has evolved with the rise of LLMs and generative AI, Data Scientists who combine traditional statistical skills with modern AI techniques are in especially high demand. The broader AI job market saw 35,445 openings in Q1 2025 alone, up 25.2% year-over-year, indicating sustained and growing demand for data professionals.
AI Job Insights for Data Science Jobs
Salary Range (Yearly, USD)
$46K - $374K
Median $139K from 46 listings with salary data
Top Companies Hiring
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Common Roles
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