Data Science Lead Jobs in Virginia
Data Science Lead jobs in Virginia are in strong demand, concentrated in defense contracting, federal consulting, financial services, and technology, with openings at every level from senior analyst stepping into a lead role through experienced principal and director-level candidates. The heaviest hiring activity is in the Northern Virginia corridor, Richmond, and the Hampton Roads area, where established employers like Booz Allen Hamilton, Capital One, and Leidos consistently bring on data science leads. The most sought-after specialties in Virginia listings are machine learning engineering, natural language processing, and cloud-based analytics. 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 Lead Jobs in Virginia
Find roles in Virginia that match your experience and apply in just a few clicks.
Find Data Science Lead JobsData Science Lead Jobs by City in Virginia
Where Virginia roles are concentrated, by current openings.
Data Science Lead 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 lead 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 leading a team or project
- Proficiency in Python or R and experience with machine learning frameworks such as TensorFlow or PyTorch
- Experience with cloud platforms including AWS, Azure, or Google Cloud in a production environment
- Ability to obtain or current possession of a federal security clearance for defense and government roles
- Strong communication skills to translate analytical findings for non-technical stakeholders and executive leadership
Data Science Lead Jobs in Virginia: Frequently Asked Questions
How do you become a data science lead in Virginia?
There is no state-issued license required to work as a data science lead in Virginia, so the path runs through education and demonstrated experience. Most Virginia employers expect a bachelor's degree in a quantitative field and several years of hands-on data science work before a lead title is considered. Northern Virginia's dense defense and federal IT market means that obtaining or maintaining a security clearance significantly strengthens candidacy, and industry certifications from AWS, Google Cloud, or Microsoft Azure are frequently cited in job postings.
How much do data science leads make in Virginia?
Data science leads in Virginia earn a median of about $126,430 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $76,420 for the lowest 10% to over $207,890 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data science leads in Virginia?
Employers hiring data science leads in Virginia right now include Capital One, Deloitte, and Information Technology Senior Management Forum, based on current listings on Migrate Mate as of September 2026. Virginia's combination of large federal contractors headquartered in Northern Virginia and major financial and healthcare institutions in Richmond and Hampton Roads makes it one of the more consistently active states for this role.
Which Virginia cities have the most data science lead jobs?
The cities with the most data science lead openings in Virginia are McLean, Richmond, and Rosslyn. Northern Virginia's concentration of federal agencies, defense contractors, and technology firms drives the bulk of postings, while Richmond's financial services sector and Hampton Roads' military and logistics base account for steady hiring in those metros.
Are there remote data science lead jobs in Virginia?
Yes, and more than most fields, since data science lead work is fundamentally analytical and collaborative through digital tools. About 38% of data science lead openings tied to Virginia are remote or hybrid as of September 2026, reflecting how broadly the role lends itself to distributed work. Model development, analysis, and team management meetings are the functions most commonly performed remotely, though roles tied to classified federal projects typically require an on-site presence in Northern Virginia.
How can I get hired as a data science lead in Virginia with little or no experience?
The most realistic entry path is moving into a data scientist or senior data analyst role first and building toward a lead title, rather than applying directly to lead positions. Virginia's large federal contractors, including firms in the Northern Virginia corridor, frequently hire junior and mid-level data scientists through new graduate programs and rotational analyst tracks that build leadership exposure. Candidates who complete a master's degree at a Virginia institution such as Virginia Tech or George Mason and pair it with a cloud certification have a measurable edge in the hiring pool for eventual lead openings.
Where can I find and apply to data science lead jobs in Virginia?
You can find and apply to data science lead jobs in Virginia on Migrate Mate, which lists current Virginia openings updated regularly. Search the listings for the location, specialization, or experience level that fits your background, then apply directly to the roles that match.
See All 52 Data Science Lead Jobs in Virginia
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