2027 Data Science Internship - United States, PhD or Masters Student
Intern
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Looking for a data scientist job in Seattle? Choose from 20 open roles at 9 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.
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As of 23 September, 21 data scientist roles are open in Seattle at 9 employers. 2 new roles have been posted since 21 September. Of the roles that say how they work, 14% are remote or hybrid.
Among data scientist roles listed on the board for Seattle, the majority are pitched at senior level, with a notable share at lead level and a small minority aimed at interns. Most openings were posted some time ago, with a smaller portion arriving within the past month and a fresh handful appearing this week or last. Hiring appears concentrated among a relatively small number of employers, with most listed roles sitting across just a handful of organisations. Python, SQL and statistics feature in nearly every description, while A/B testing appears in roughly half. A smaller but meaningful share of descriptions mention large language models and related skills, reflecting the broad influence of AI work across Seattle's technology sector. There is not yet enough weekly history to describe any direction of change over time.
Figures are measured every Monday.
Data scientists draw on statistical methods, programming and domain knowledge to extract meaning from large datasets, build predictive models and inform decisions. Day-to-day work typically spans exploratory analysis, feature engineering, model development and communicating findings to non-technical stakeholders. Seattle's technology landscape, anchored by major e-commerce, cloud and software operations, as well as a growing presence in life sciences and health services, means data scientists here tend to work across product, operations and research contexts. Organisations such as Ai2 carry out open research using data science methods, and the University of Washington's Institute for Protein Design applies computational approaches including AI models to biological problems. Teams are generally cross-functional, pairing data scientists with engineers, product managers and analysts.
Python and SQL appear in virtually every description, making both effectively baseline expectations. Statistics appears alongside them at a similar frequency, pointing to a grounding in quantitative methods. A/B testing features in about half of descriptions, suggesting experimentation and causal inference matter to many teams. Spark appears in roughly a quarter of descriptions, as do references to large language models, signalling that distributed data processing and generative AI work both appear in a meaningful share of roles.
The employers' own advertised ranges, for individual roles at different levels — not an average and not a market rate.
On-site work dominates strongly among the roles listed here that state a location arrangement, with the large majority requiring presence in Seattle. A small share offer hybrid arrangements. None of the roles stating a preference are listed as fully remote, so candidates should be prepared for regular in-person attendance.
Jobs checked 8 hours ago. · Guide reviewed 14 September 2026.
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