Staff Applied Scientist Jobs
Staff Applied Scientist jobs are open across technology, healthcare, financial services, and e-commerce, from senior individual contributor to staff and principal levels, with specializations in machine learning, natural language processing, and recommendation systems. See the openings below and apply to the ones that match your experience.
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Showing 5 of 529+ Staff Applied Scientist jobs
DESCRIPTION
Amazon Web Services (AWS) provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world.
We are hiring an Applied Scientist in our AWS Sales Science & Economics team. The team uses machine learning, econometrics, and data science to optimize AWS’s service catalogue, driving customer engagement and generating insights to guide AWS sales strategy. We use detailed customer behavioral and usage data to predict and understand what customers want from AWS.
Key job responsibilities
As an Applied Scientist, you will apply the latest research, state of the art machine learning and GenAI to build highly scalable models in support of predictive research and products used across AWS Sales and leadership. You will be responsible for designing and executing science experiments in short and agile cycles. You will use the latest AWS technologies in Machine Learning, Data Science, and AI. You will work closely with business leaders to identify opportunities to drive business growth by applying machine learning and building out predictive models to support analytics and insights.
The ideal candidate will be curious and able to learn new technologies quickly. You will have hands-on experience building data science and machine learning pipelines in production working with large scale data sets. You are passionate about sharing your knowledge to enable others. You empathize with the needs of our customers and align your work accordingly, and provide thought leadership and guidance across the organization.
A day in the life
You will start your day reviewing experimental results and refining model architectures based on new insights. You might spend the morning prototyping a novel approach to a customer-facing problem, then shift to a design review with engineering partners in the afternoon to align on how your solution integrates into production systems. Along the way, you will mentor junior scientists, contribute to peer reviews, and stay connected to the latest research through reading groups and internal science discussions. Your contributions will move from research notebooks to live systems that customers interact with every day.
About the team
Our team is focused on applying advanced science and machine learning to build intelligent systems that improve the Amazon experience. We value collaboration, intellectual rigor, and a willingness to explore new ideas. You will work alongside scientists and engineers who are committed to turning ambitious research into practical, high-impact solutions. We are investing in the next generation of machine learning capabilities and are looking for team members who are excited to help define that future.
BASIC QUALIFICATIONS
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience in professional software development
- Currently has, or is in the process of obtaining, a PhD in computer science, machine learning, engineering, or related fields
- Have publications at top-tier peer-reviewed conferences or journals
- Experience in solving business problems through machine learning, data mining and statistical algorithms
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
DESCRIPTION
Amazon Web Services (AWS) provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world.
We are hiring an Applied Scientist in our AWS Sales Science & Economics team. The team uses machine learning, econometrics, and data science to optimize AWS’s service catalogue, driving customer engagement and generating insights to guide AWS sales strategy. We use detailed customer behavioral and usage data to predict and understand what customers want from AWS.
Key job responsibilities
As an Applied Scientist, you will apply the latest research, state of the art machine learning and GenAI to build highly scalable models in support of predictive research and products used across AWS Sales and leadership. You will be responsible for designing and executing science experiments in short and agile cycles. You will use the latest AWS technologies in Machine Learning, Data Science, and AI. You will work closely with business leaders to identify opportunities to drive business growth by applying machine learning and building out predictive models to support analytics and insights.
The ideal candidate will be curious and able to learn new technologies quickly. You will have hands-on experience building data science and machine learning pipelines in production working with large scale data sets. You are passionate about sharing your knowledge to enable others. You empathize with the needs of our customers and align your work accordingly, and provide thought leadership and guidance across the organization.
A day in the life
You will start your day reviewing experimental results and refining model architectures based on new insights. You might spend the morning prototyping a novel approach to a customer-facing problem, then shift to a design review with engineering partners in the afternoon to align on how your solution integrates into production systems. Along the way, you will mentor junior scientists, contribute to peer reviews, and stay connected to the latest research through reading groups and internal science discussions. Your contributions will move from research notebooks to live systems that customers interact with every day.
About the team
Our team is focused on applying advanced science and machine learning to build intelligent systems that improve the Amazon experience. We value collaboration, intellectual rigor, and a willingness to explore new ideas. You will work alongside scientists and engineers who are committed to turning ambitious research into practical, high-impact solutions. We are investing in the next generation of machine learning capabilities and are looking for team members who are excited to help define that future.
BASIC QUALIFICATIONS
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience in professional software development
- Currently has, or is in the process of obtaining, a PhD in computer science, machine learning, engineering, or related fields
- Have publications at top-tier peer-reviewed conferences or journals
- Experience in solving business problems through machine learning, data mining and statistical algorithms
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
Staff Applied Scientist Jobs by Experience Level
See All 529+ Staff Applied Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find Staff Applied Scientist JobsStaff Applied Scientist Job Market
Who's Hiring
- Amazon245
- Amazon Web Services52
- Microsoft24
- TikTok18
- Apple16
Top Industries Hiring
- Technology & Software72
- Retail35
- E-Commerce & Online Marketplaces30
- Distribution & Wholesale5
- Electronics & Hardware4
What Employers Look For
The qualifications that appear most often in staff applied scientist jobs.
- PhD or Master's degree in computer science, statistics, or a related quantitative field
- 5 or more years of applied machine learning experience building and deploying production models
- Proficiency in Python and core ML frameworks such as PyTorch or TensorFlow
- Experience with large-scale distributed computing platforms such as Spark or cloud ML services
- Demonstrated ability to lead technical projects and mentor junior scientists or engineers
- Strong communication skills for presenting model results and trade-offs to non-technical stakeholders
Tips for Your Staff Applied Scientist Job Search
Quantify model impact on your resume
Staff-level roles expect you to show business outcomes, not just technical methods. Replace vague descriptions with concrete metrics: latency reductions, accuracy lifts, or revenue impact. Hiring managers at this level read dozens of PhD resumes and skip ones without measurable results.
Distinguish applied from research roles
Many staff applied scientist postings require production deployment experience, not just research publications. Read each job description closely for terms like 'model serving,' 'A/B testing,' or 'cross-functional collaboration,' which signal they want someone who ships, not just publishes.
Apply early to roles that fit
Migrate Mate lists staff applied scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target companies by ML maturity stage
Early-stage companies want applied scientists who build infrastructure from scratch. Mature teams want specialists who optimize existing systems. Scan the job description for whether the team is building foundations or iterating on deployed models, then tailor your resume narrative accordingly.
Prepare a system design answer for ML
Staff applied scientist interviews almost always include an ML system design round where you architect a recommendation engine, ranking system, or search pipeline end to end. Practice narrating trade-offs out loud, not just drawing diagrams, because interviewers probe your reasoning at each step.
Negotiate scope alongside compensation
At the staff level, your mandate, team size, and roadmap influence are negotiable, not just your pay band. Before your final offer call, clarify what your first six months look like, which projects you own, and whether the role has a path to principal or research scientist.
Staff Applied Scientist Jobs: Frequently Asked Questions
Which companies are hiring the most staff applied scientists?
The companies hiring the most staff applied scientists right now include Amazon, Amazon Web Services, and Microsoft, with the largest share of openings in Washington, California, and New York, based on current listings on Migrate Mate as of November 2026. Technology and financial services companies consistently account for the largest share of staff-level postings.
How many staff applied scientist jobs are remote?
About 47% of staff applied scientist openings are fully remote or hybrid as of November 2026, reflecting the role's reliance on collaborative experimentation and cross-functional partnerships. Sub-areas focused on natural language processing and search ranking tend to have the highest concentration of remote-eligible postings, while roles tied to real-time systems or hardware often require on-site presence.
How do you become a staff applied scientist?
Start by building a foundation in machine learning through a graduate degree or rigorous self-study, then gain industry experience deploying models in production environments. Progress from applied scientist to senior applied scientist by owning end-to-end projects, then earn the staff designation by demonstrating cross-team technical leadership, mentoring junior scientists, and driving measurable business impact at scale.
Can you get hired as a staff applied scientist without direct experience?
Moving directly into a staff applied scientist role with no industry experience is uncommon because employers expect production deployment history and evidence of technical leadership. Candidates coming from academia can bridge the gap by contributing to open-source ML projects, publishing applied work with clear real-world benchmarks, and targeting companies with structured research-to-industry transition programs.
What does the staff applied scientist interview process look like?
Most staff applied scientist interview processes include a recruiter screen, a technical phone round covering coding and probability or statistics, an ML system design session where you architect a full pipeline, and a behavioral round assessing leadership and cross-functional influence. Final loops typically involve multiple back-to-back sessions with scientists, engineers, and product managers, followed by a hiring committee review before an offer is extended.
Where can I find and apply to staff applied scientist jobs?
You can find and apply to staff applied scientist jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background in machine learning, your preferred industry, and your target location, then apply directly to each listing that fits.
See All 529+ Staff Applied Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find Staff Applied Scientist Jobs