Data Science Manager Jobs in Virginia
Data Science Manager jobs in Virginia are concentrated in the Northern Virginia technology corridor, Richmond, and the Hampton Roads region, where federal agencies, defense contractors, and financial institutions drive consistent demand for leaders who can manage machine learning pipelines, analytics teams, and data governance programs. Booz Allen Hamilton, Capital One, and Leidos maintain large Virginia footprints and regularly hire data science managers with expertise in cloud-native platforms, NLP, and applied AI. The market ranks among the most active in the mid-Atlantic for senior data and analytics leadership. Find a role that fits below and apply directly.
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DESCRIPTION
Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.
The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions, improving the availability, reliability, latency, performance and efficiency to operate AWS regions.
The AWS Managed Operations Intelligence (MOI) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration, ETL, model development and data visualization. You will leverage a broad set of tools and technologies, including general analytical frameworks (Spark, Airflow, etc.), AI frameworks (Hugging Face, etc.) and various machine learning frameworks, to tackle complex business problems.
Your analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale, and you are comfortable working with cross-functional teams and systems.
By working together on behalf of our customers, we are building the future one innovative product, service, and idea at a time. Are you ready to embrace the challenge? Come build the future with us.
Key job responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical approaches
- Develop ML/AI models. Partner with software teams to productionalize these models.
- Data Pipeline and Infrastructure: design and implementation of data pipelines
- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics
A day in the life
Why AWS?
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
About AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events create stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
About the team
The Managed Operations Intelligence (MOI) Team helps AWS operate its services across the world. We help monitor AWS operations by providing insights and recommendations on AWS operations.
BASIC QUALIFICATIONS
- 3+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
PREFERRED QUALIFICATIONS
- 6+ years of data scientist experience
- 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience in a ML or data scientist role with a large technology company
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, VA, Arlington - 136,000.00 - 184,000.00 USD annually
DESCRIPTION
Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.
The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions, improving the availability, reliability, latency, performance and efficiency to operate AWS regions.
The AWS Managed Operations Intelligence (MOI) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration, ETL, model development and data visualization. You will leverage a broad set of tools and technologies, including general analytical frameworks (Spark, Airflow, etc.), AI frameworks (Hugging Face, etc.) and various machine learning frameworks, to tackle complex business problems.
Your analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale, and you are comfortable working with cross-functional teams and systems.
By working together on behalf of our customers, we are building the future one innovative product, service, and idea at a time. Are you ready to embrace the challenge? Come build the future with us.
Key job responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical approaches
- Develop ML/AI models. Partner with software teams to productionalize these models.
- Data Pipeline and Infrastructure: design and implementation of data pipelines
- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics
A day in the life
Why AWS?
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
About AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events create stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
About the team
The Managed Operations Intelligence (MOI) Team helps AWS operate its services across the world. We help monitor AWS operations by providing insights and recommendations on AWS operations.
BASIC QUALIFICATIONS
- 3+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
PREFERRED QUALIFICATIONS
- 6+ years of data scientist experience
- 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience in a ML or data scientist role with a large technology company
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, VA, Arlington - 136,000.00 - 184,000.00 USD annually
See All 52 Data Science Manager Jobs in Virginia
Find roles in Virginia that match your experience and apply in just a few clicks.
Find Data Science Manager JobsData Science Manager Jobs by City in Virginia
Where Virginia roles are concentrated, by current openings.
Data Science Manager Job Market in Virginia
A snapshot from current Virginia openings, updated as new roles post.
Who's Hiring
- Capital One10
- Deloitte6
- Information Technology Senior Management Forum5
- CarMax3
- Peraton3
Top Industries Hiring
- Banking & Financial Services
- Education
- Science & Research
- Technology & Software
- Consulting & Professional Services
What Virginia Employers Look For
The qualifications that appear most often in data science manager jobs across Virginia.
- Bachelor's or master's degree in data science, statistics, computer science, or a related quantitative field
- Five or more years of data science experience with at least two years in a team lead or management role
- Proficiency in Python or R and experience deploying machine learning models in production environments
- Demonstrated ability to translate complex analytical findings into actionable guidance for non-technical stakeholders
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud in an enterprise environment
- Strong project management skills with a history of delivering data products on schedule and within scope
Data Science Manager Jobs in Virginia: Frequently Asked Questions
How do you become a data science manager in Virginia?
The most direct path is a bachelor's or master's degree in a quantitative discipline such as statistics, computer science, or applied mathematics, followed by several years as an individual-contributor data scientist before moving into team leadership. Virginia has no state-issued license or registration specific to data science management. Many Virginia employers, particularly defense contractors in Northern Virginia, also value a security clearance, which becomes an informal differentiator for candidates targeting federal-facing roles.
Which companies hire data science managers in Virginia?
Companies currently hiring data science managers in Virginia include Capital One, Deloitte, and Information Technology Senior Management Forum, per current listings on Migrate Mate as of September 2026. Northern Virginia's concentration of defense contractors, federal consulting firms, and financial services companies makes it one of the most consistent sources of data science leadership openings in the state.
Which Virginia cities have the most data science manager jobs?
McLean, Richmond, and Rosslyn account for the largest share of data science manager openings in Virginia. Northern Virginia dominates because of its dense cluster of federal agencies, defense contractors, and technology companies, while Richmond draws hiring from major financial institutions and healthcare systems, and Hampton Roads openings are largely tied to defense and naval research employers based in the region.
Are there remote data science manager jobs in Virginia?
Yes, and more than most fields. Data science management is largely analytical and communication-based work, making it well suited to remote and hybrid arrangements. About 38% of data science manager openings tied to Virginia are remote or hybrid as of September 2026, with strategy, modeling oversight, and stakeholder reporting being the functions most commonly performed off-site. Roles requiring a security clearance or close collaboration with on-site engineering teams are more likely to require regular in-person presence.
How can I get hired as a data science manager in Virginia with little or no experience?
The most realistic entry path is building management exposure as a senior data scientist or technical lead before applying to formal manager roles. Virginia's large consulting firms, including those concentrated in the Tysons and Reston corridors, regularly hire associate or staff data scientists into project-based environments where leadership opportunities emerge quickly. Building a portfolio of end-to-end ML projects, contributing to open-source repositories, and earning a cloud certification through AWS or Azure adds credibility when competing for first-time manager positions at mid-size Virginia technology and analytics firms.
Where can I find and apply to data science manager jobs in Virginia?
You can find and apply to data science manager jobs in Virginia on Migrate Mate, which lists current Virginia openings updated regularly. Find roles that fit your background and apply directly to the employers posting them.
See All 52 Data Science Manager Jobs in Virginia
Find roles in Virginia that match your experience and apply in just a few clicks.
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