Applied Science Manager Jobs
Applied Science Manager jobs are open across technology, healthcare, finance, and e-commerce, from senior individual contributor to director level, with common specializations in machine learning, natural language processing, and computer vision. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 111+ Applied Science Manager 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
See All 111+ Applied Science Manager Jobs
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Find Applied Science Manager JobsApplied Science Manager Job Market
Who's Hiring
- Amazon60
- Amazon Web Services8
- The Hartford4
- William & Mary4
- Shure3
Top Industries Hiring
- Retail
- Education
- Technology & Software
- E-Commerce & Online Marketplaces
- Biotechnology & Pharmaceuticals
What Employers Look For
The qualifications that appear most often in applied science manager jobs.
- Master's or PhD in computer science, statistics, or a related quantitative field
- Proven experience managing and mentoring a team of applied scientists or ML researchers
- Deep hands-on expertise in machine learning, deep learning, or statistical modeling
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Experience translating ambiguous business problems into end-to-end ML solutions at scale
- Strong cross-functional communication with product, engineering, and business stakeholders
Tips for Your Applied Science Manager Job Search
Quantify your team and model impact
Applied science manager resumes that land interviews pair team size with measurable outcomes, like how many scientists you led and what your models actually moved in revenue, latency, or accuracy. Generic leadership bullets get skipped.
Distinguish science leadership from engineering management
Many listings conflate applied science managers with ML engineering managers. Tailor your resume to show you own the research roadmap and publication or patent outputs, not just deployment pipelines, so hiring teams slot you into the right level.
Apply early to roles that fit
Migrate Mate lists applied science manager openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target listings that name your modeling domain
Applied science manager roles in recommendation systems, search relevance, and forecasting require different depth. Search for openings that name your core domain, then confirm in the job description that the team owns that problem end to end.
Prepare a research-to-product narrative
Interviewers for applied science manager roles probe how you move work from experiment to production at scale. Prepare two or three stories where you drove the decision to ship, kill, or pivot a project, with clear business reasoning behind each call.
Negotiate scope alongside compensation
Applied science manager offers vary widely on headcount, compute budget, and publishing autonomy. Before accepting, confirm team size, whether you can publish or file patents, and what your model owns in the product stack, not just base and equity.
Applied Science Manager Jobs: Frequently Asked Questions
Which companies are hiring the most applied science managers?
The companies hiring the most applied science managers right now include Amazon, Amazon Web Services, and The Hartford, with the largest share of openings in Washington, California, and New York, based on current listings on Migrate Mate as of November 2026. Large technology companies and cloud platform providers consistently account for the majority of open roles.
How many applied science manager jobs are remote?
About 57% of applied science manager openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed science leadership. Roles focused on natural language processing, recommendation systems, and search tend to offer remote arrangements more often than positions embedded in hardware or robotics programs that require on-site lab access.
How do you become an applied science manager?
Start by building deep individual contributor credibility as an applied scientist or ML engineer, shipping models with measurable business impact. Take on informal mentorship and project coordination before pursuing a formal management role. Develop a point of view on research prioritization, then apply to teams where the manager role is a natural extension of your domain expertise rather than a pure career pivot.
Can you get hired as an applied science manager with little management experience?
Yes, if your individual contributor record is strong enough to anchor the case for promotion. Hiring teams often consider senior applied scientists who have informally led projects, onboarded junior colleagues, or driven cross-functional work, even without direct reports. Framing past influence, mentorship, and technical decision-making as leadership evidence helps close the gap when formal management history is thin.
What does the applied science manager interview process look like?
Most processes run across four to five rounds covering a technical screen, a system design or modeling discussion, a research presentation where you walk through past work in depth, a leadership and behavioral round, and a cross-functional or executive conversation. Some companies also include a written case study on how you would staff, scope, or prioritize a science roadmap given limited resources and competing product demands.
Where can I find and apply to applied science manager jobs?
You can find and apply to applied science manager jobs on Migrate Mate, which lists current openings from companies across the United States. Search the roles available, find the ones that match your background and target domain, and apply directly to each listing that fits.
See All 111+ Applied Science Manager Jobs
Find roles that match your experience and apply in just a few clicks.
Find Applied Science Manager Jobs