Mid Level Research Data Scientist Jobs
Mid level research data scientist jobs go to researchers ready to own studies end to end, make analytical decisions with limited oversight, and mentor junior team members on methodology and best practices. Roles run across Electronics & Hardware, Education, and Science & Research, with a strong mix of remote and on-site positions, and employers like Apple, Google, and OpenAI hiring at this level now.
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Would you like to join a team curious about understanding how foundation models work and to expand their capabilities in scientific domains? We perform and publish novel research and apply our findings to drive product directions. If you like designing clever approaches to understanding complex phenomena and using that knowledge to solve practical problems then this is the position for you.
Description
In this research scientist role you will join a small team of researchers performing fundamental research investigating foundation models for scientific domains. You will be involved in all aspects of performing research including project definition, method development, and experimental design. You will also run your own experiments, then analyze and interpret the results. You will take an active role in writing papers for publication and also using our findings to solve applied problems. You will also have the opportunity to collaborate with partner teams across Apple.
","responsibilities":"Design robust experiments and methods to understand what foundation models do under the hood.
Implement your methods and designs in experiment pipelines.
Analyze and interpret your experimental results.
Communicate results to teams across Apple.
Write papers for publication in top-tier conferences/journals.
Preferred Qualifications
Experience with large language models and - both training them and using tools like vllm for inference.
Proficient implementing ML models and experiments in Python and Pytorch/Jax.
Familiarity with interpretability methods like activation patching/causal tracing.
Demonstrate the ability to refine ambiguous research ideas to construct a coherent and logically sound story.
Minimum Qualifications
PhD in computer science, statistics, physics, chemistry, electrical engineering, or operations research. Other hard sciences may also be considered.
3 publications in top-tier machine learning, statistics, or natural language processing venues.
Deep knowledge of foundation models and experience training them and applying them to real, complex datasets as demonstrated through publications or code repositories.
Experience designing experiments to understand how foundation models work.
Knowledge of Bayesian statistical methods and how they are used for scientific inference.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,000 and $308,500, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Top Industries Hiring
- Electronics & Hardware
- Education
- Science & Research
- Healthcare & Medical Services
Mid Level Research Data Scientist Jobs: Frequently Asked Questions
How do I get a mid level research data scientist job?
Position your experience around ownership, not just contribution. Highlight projects where you drove the analytical direction, chose methods independently, or translated findings into decisions. Tailor your application materials to show depth in a specific domain, whether that is NLP, causal inference, or experiment design, and make your impact measurable with outcomes rather than tasks.
Which companies hire mid level research data scientists?
Companies hiring mid level research data scientists right now include Apple, Google, and OpenAI, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a broad mix of technology firms, research-driven enterprises, and organizations building internal data science functions with enough scale to support dedicated research roles.
Are there remote mid level research data scientist jobs?
Yes, remote and hybrid availability is strong at this level. About 33% of mid level research data scientist openings are remote or hybrid as of September 2026, reflecting how research-focused work translates well to distributed settings. On-site roles tend to appear more often in industries where collaboration with lab teams or proprietary data environments is required.
How do I move up to a mid level research data scientist role?
The path from entry level to mid level is built on demonstrated ownership over time. Focus on taking full responsibility for discrete projects, deepening expertise in a technical area like statistical modeling or machine learning, and showing that your work influenced real decisions. Consistent delivery, clear communication of findings, and the ability to work without close supervision are what distinguish mid level candidates from junior ones.
Which industries hire the most mid level research data scientists?
Mid Level research data scientist roles concentrate in Electronics & Hardware, Education, and Science & Research, based on current listings on Migrate Mate as of September 2026. These sectors tend to drive hiring at this level because they generate complex, high-volume data problems that require researchers who can operate independently and move work from question to insight without heavy supervision.