Applied Data Scientist Jobs
Applied Data Scientist jobs are open across technology, healthcare, finance, and retail, from new-grad to principal and staff levels, with specializations in NLP, computer vision, and predictive modeling. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 539+ Applied Data 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
Applied Data Scientist Jobs by Experience Level
See All 539+ Applied Data Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find Applied Data Scientist JobsApplied Data Scientist Job Market
Who's Hiring
- Amazon248
- Amazon Web Services56
- Microsoft24
- TikTok21
- Apple16
Top Industries Hiring
- Technology & Software75
- Retail35
- E-Commerce & Online Marketplaces30
- Distribution & Wholesale6
- Electronics & Hardware4
What Employers Look For
The qualifications that appear most often in applied data scientist jobs.
- Proficiency in Python and SQL for data manipulation and model development
- Experience building and deploying machine learning models in production environments
- Familiarity with cloud platforms such as AWS, GCP, or Azure for ML workloads
- Strong knowledge of statistical modeling, A/B testing, and experimental design
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related field
- Experience with MLOps tooling including model monitoring, versioning, and pipeline orchestration
Tips for Your Applied Data Scientist Job Search
Tailor your resume to production context
Applied data scientist roles prioritize end-to-end deployment experience over exploratory analysis. For each position, your resume should show models you shipped to production, the business metric they moved, and the infrastructure you used to get them there.
Show your code, not just your credentials
Hiring managers for applied roles expect a public code repository. Push at least two end-to-end projects that include data ingestion, feature engineering, model training, and an inference API, so reviewers can read your actual engineering decisions.
Apply early to roles that fit
Migrate Mate lists applied data scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by tech stack before applying
Job descriptions for applied roles are specific about MLOps tooling. If a posting requires SageMaker, Vertex AI, or a particular orchestration framework you haven't used, flag that gap before applying so you can address it directly in your cover materials.
Prepare a system design answer for ML
Applied data scientist interviews almost always include an ML system design round. Practice walking through feature stores, training pipelines, model serving, and monitoring for a realistic use case in the target company's domain before your first screen.
Negotiate on scope, not just compensation
When you receive an offer, ask which team owns model deployment and what your on-call responsibilities look like. Applied roles vary widely in how much of the production stack you own, and those details affect day-to-day workload as much as the base salary does.
Applied Data Scientist Jobs: Frequently Asked Questions
Which companies are hiring the most applied data scientists?
Amazon, Amazon Web Services, and Microsoft are hiring the most applied data scientists right now, with openings concentrated in Washington, California, and New York, based on current listings on Migrate Mate as of November 2026. Demand is especially high at companies with large consumer-facing platforms that rely on real-time recommendation and ranking systems.
How many applied data scientist jobs are remote?
About 48% of applied data scientist openings are fully remote or hybrid as of November 2026, reflecting the role's heavy reliance on cloud-based tooling and collaborative notebooks. Sub-areas such as NLP research and recommendation systems tend to have the highest share of fully remote positions, while roles tied to on-device or hardware-adjacent ML are more likely to require on-site presence.
How do you become an applied data scientist?
Start by building a foundation in linear algebra, probability, and statistics, then develop practical Python and SQL skills through real projects. Work on end-to-end pipelines that go from raw data to a deployed model, document them publicly, and practice communicating results to a non-technical audience. Industry internships or research roles that involve production systems accelerate the transition considerably.
Can you get hired as an applied data scientist with little experience?
Yes, but your portfolio needs to substitute for tenure. Build two or three projects that demonstrate the full applied workflow: data cleaning, feature engineering, model selection, evaluation, and a simple serving layer. Contribute to open-source ML libraries, write up your findings clearly, and target companies with structured new-grad programs in their ML or data science organizations.
What does the applied data scientist interview process look like?
Most applied data scientist interview processes include a recruiter screen, a take-home or live coding assessment in Python, a statistics and probability round, and an ML system design session. Final rounds typically add a business case discussion where you are expected to frame a modeling problem from a product metric and defend your approach to both technical and non-technical stakeholders.
Where can I find and apply to applied data scientist jobs?
You can find and apply to applied data scientist jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that match your background and target industry, and apply directly to each listing from the page.
See All 539+ Applied Data Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
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