In 2026, the median base salary for a Data Scientist is $185K. Based on our analysis of 1,000 real job postings, salaries typically range from $152K at the 25th percentile to $218K at the 75th percentile, reflecting differences in experience, location, and company stage.
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Work with us → Browse open rolesBased on an analysis of 1,000 Data Scientist job postings scraped from company career pages, the median base salary for Data Scientists in 2026 stands at $185K. This figure comes from our proprietary database of over 1.9 million job postings.
Salaries for Data Scientists vary significantly depending on experience, specific skill sets, and the company's stage and location. Entry to mid-level roles typically fall around the 25th percentile, earning approximately $152K. More experienced Data Scientists, often taking on more complex projects or leadership responsibilities, command salaries closer to the 75th percentile, around $218K.
This range isn't just about years on the job. It also reflects the increasing demand for specialized skills, such as expertise in machine learning engineering for production systems, large language models, or advanced statistical modeling. A Data Scientist who can not only build models but also deploy them and measure their business impact will generally earn more.
Location remains a significant factor in Data Scientist compensation, though the rise of remote work has shifted some of the traditional premiums.
Our data shows that the median base salary for a Data Scientist in San Francisco is $210K. This represents a 9% premium compared to the median remote Data Scientist salary of $192K. This difference largely reflects the higher cost of living in the Bay Area and the concentration of well-funded, high-growth technology companies that often pay top dollar to attract talent.
While the San Francisco premium is still notable, the gap has narrowed compared to a few years ago. Remote salaries have climbed as companies outside traditional tech hubs compete for talent and as candidates prioritize flexibility. For Data Scientists, working remotely often means access to a broader market of employers, and for companies, it means access to a wider pool of talent, potentially leading to more competitive remote compensation packages.
Several factors beyond basic experience levels dictate whether a Data Scientist's compensation lands at the higher or lower end of the spectrum:
The Data Scientist role has seen significant evolution in compensation, particularly influenced by the broader AI boom. For a period, salaries surged as companies scrambled to build out their data capabilities and keep pace with advancements in machine learning. Many organizations realized the strategic importance of data-driven decision-making and invested heavily in talent.
In 2026, we see a more mature, though still growing, market for Data Scientists. The initial hyper-growth in salaries has somewhat stabilized, but compensation remains robust, especially for those with specialized skills in areas like generative AI, large language models, or production-grade ML systems. The market is less about hiring any Data Scientist and more about identifying those who can drive tangible business impact and are adept at navigating the complexities of real-world data problems. Companies are now looking for data scientists who understand the full lifecycle from data ingestion to model deployment and monitoring, pushing salaries higher for full-stack data science talent.
Recruiting from Scratch is a software-driven recruiting firm that places talent across all functions at high-growth companies from seed-stage startups to large public companies like Palantir. Since our founding in 2019, we've completed 300+ placements at over 150 unique organizations.
Our insights come from real, current data:
When opening a Data Scientist requisition, understanding current market compensation is critical to attracting and closing top talent. Offering a salary that is not competitive with the median or above will likely result in a slow process and a struggle to secure pre-qualified candidates. Focus your compensation packages on the upper quartile for critical roles, especially if you're seeking specialized skills or experience in a competitive location like San Francisco. Equity is a significant component, particularly for earlier-stage companies, but cash must still meet market expectations. For more insights on competitive compensation, visit our employers page.
The median base salary for a Data Scientist in 2026 is $185K. Salaries typically range from $152K at the 25th percentile to $218K at the 75th percentile, based on our analysis of 1,000 real job postings.
At seed-stage startups, Data Scientists might receive a lower cash salary compensated by higher equity. Larger, more established companies, including public companies, generally offer more competitive cash compensation with a still meaningful equity component, especially for senior roles.
Junior Data Scientists often fall around the 25th percentile, earning about $152K. Senior and Staff-level Data Scientists with significant experience and impact can expect salaries closer to the 75th percentile, around $218K, or even higher for Principal roles.
Data Scientist salaries are generally higher in San Francisco, with a median of $210K, which is 9% above the median remote salary of $192K. This premium is largely due to the higher cost of living and concentration of well-funded tech companies in the Bay Area.
Skills that significantly increase a Data Scientist's salary include expertise in production machine learning, MLOps, deep learning frameworks, large language models, and cloud platforms. The ability to translate complex models into direct, measurable business value also commands a premium.
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