Develop and optimize machine learning models for analyzing unstructured text, image, and video data for an investigative platform. Collaborate with cross-functional teams to design scalable predictive systems and guide data pipeline architecture.
Remote Data Scientist Salary – updated July 2026
The average salary for remote data scientist is $120,000 per year. This is based on data from 812 job openings.
Where do you get the data from?
Data is based on 812 job openings.
How much does a Data Scientist make?
The salary range for data scientist is anywhere between $70,000 to $200,000 per year.
Can you provide a breakdown of salary data by years of experience?
Below is a breakdown of salary data by years of experience:
| EXPERIENCE | MINIMUM SALARY | AVERAGE SALARY | MAXIMUM SALARY |
|---|---|---|---|
| Entry Level Data Scientist (0-1 years) | $70,000 | $82,500 | $95,000 |
| Mid Level Data Scientist (2-4 years) | $95,000 | $112,500 | $130,000 |
| Senior Level Data Scientist (5-9 years) | $130,000 | $145,000 | $160,000 |
| Lead Level Data Scientist (10+ years) | $160,000 | $180,000 | $200,000 |
* Data is based on 812 job openings.
What is the salary range for remote Entry-Level Data Scientist?
The salary range for entry-level data scientist is between $70,000 and $95,000 per year.
What is the salary range for remote Senior-Level Data Scientist?
The salary range for senior-level data scientist is between $130,000 and $160,000 per year.
Can Data Scientist be fully remote?
Yes, Data Scientist positions can be fully remote. Companies such as Thomson Reuters, McGraw Hill LLC., ABC Legal Services are hiring remotely for Data Scientist. Check out the latest remote Data Scientist job openings below.
Are there any remote job openings for Data Scientist?
Yes, there are 812 remote job openings:
The Data Scientist will research, analyze, and model data to deliver cutting-edge AI solutions for the Higher Education business unit. They will collaborate with cross-functional teams to create and execute generative AI projects that enhance educational experiences.
Own the full machine learning lifecycle from research and experimentation to deployment and monitoring using AWS SageMaker Studio. Collaborate with product and operations teams to develop models that solve business problems across legal services and marketing.
Own the full machine learning lifecycle from research and experimentation to deployment and monitoring. Collaborate with cross-functional teams to build MLOps pipelines and deliver models that drive business outcomes.
The role involves owning the full machine learning lifecycle from research and experimentation to deployment and monitoring. You will build MLOps pipelines in AWS SageMaker Studio to deliver models that drive business outcomes across operations and marketing.
The role involves designing and prototyping agentic AI systems and scalable production software to solve complex national security data problems. You will collaborate with cross-functional teams to translate customer needs into technical data science solutions and strategic product roadmaps.
Drive HR decision-making by designing and implementing machine learning models for attrition, hiring, and workforce planning. Translate complex analytical outputs into actionable business insights and build scalable data solutions using Python.
Develop and iterate on statistical and ML models for credit underwriting, risk management, and cash-flow forecasting. Own the end-to-end model lifecycle, including deployment, performance monitoring, and retraining.
Develop and maintain end-to-end ML models for flight departure delay prediction and operational forecasting. Build internal tooling for dataset generation and training pipelines while collaborating with backend teams for live system integration.
Design, train, and deploy Generative AI and ML solutions to prevent Fraud, Waste, and Abuse in healthcare claims. Build scalable ML pipelines and RAG systems while collaborating with cross-functional teams to optimize production models.
