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Data Science Lead Jobs in Virginia (NOW HIRING)

Lead cross-functional teams through the model lifecycle, aligning changes with business goals ... Master's degree in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related ...

... data-driven decisions with an objective of driving quantifiable, optimized business results in ... Lead on target initiatives as assigned; work independently to drive decision science projects ...

Lead the data science roadmap spanning personalization, recommendation systems, and GenAI chatbot development, owning strategy for user profiling, content matching, ranking, conversational AI, and ...

Lead the data science roadmap spanning personalization, recommendation systems, and GenAI chatbot development, owning strategy for user profiling, content matching, ranking, conversational AI, and ...

Lead workforce planning and staffing alignment across data science workstreams. * Establish modeling standards, peer review processes, and analytical quality governance frameworks. * Foster a ...

Lead workforce planning and staffing alignment across data science workstreams. * Establish modeling standards, peer review processes, and analytical quality governance frameworks. * Foster a ...

Lead workforce planning and staffing alignment across data science workstreams. * Establish modeling standards, peer review processes, and analytical quality governance frameworks. * Foster a ...

Lead workforce planning and staffing alignment across data science workstreams. * Establish modeling standards, peer review processes, and analytical quality governance frameworks. * Foster a ...

Lead the development and enhancement of predictive Customer Progression models * Apply advanced data science techniques across the full model lifecycle: * Design, training, evaluation, validation ...

Lead the development and enhancement of predictive Customer Progression models * Apply advanced data science techniques across the full model lifecycle: * Design, training, evaluation, validation ...

Lead the development and enhancement of predictive Customer Progression models * Apply advanced data science techniques across the full model lifecycle: * Design, training, evaluation, validation ...

Further, they Lead advanced analytics and workforce modeling efforts; oversee data science team; deliver insights for HR strategy. Lead Data Scientist Professionals typically cover Data Scientist ...

MORSE is searching for a Lead Data Scientist with expertise in data analysis, data science, and ... D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or ...

May lead with the selection of appropriate analytical approaches towards automation. Reviews and defines requirements for data science cybersecurity approaches. Data Scientist Level 3 (Senior ...

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Showing results 1-20

Data Science Lead information

See Virginia salary details

$30

$69

$95

How much do data science lead jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for data science lead in Virginia is $69.48, according to ZipRecruiter salary data. Most workers in this role earn between $60.05 and $77.93 per hour, depending on experience, location, and employer.

How does a Data Science Lead typically balance technical responsibilities with team leadership duties?

A Data Science Lead often splits their time between hands-on technical work and managing their team. While they actively contribute to model development, data analysis, and code reviews, they also spend significant time mentoring junior data scientists, coordinating project timelines, and aligning team efforts with business objectives. Effective Data Science Leads prioritize communication and delegation, ensuring the team remains innovative while meeting deadlines. This dual focus can be challenging, but it provides valuable opportunities for professional growth and impact across the organization.

What is the difference between Data Science Lead vs Data Analyst?

AspectData Science LeadData Analyst
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; often requires experience in machine learning and programmingBachelor's degree in Statistics, Mathematics, or related fields; focus on data interpretation and reporting
Work EnvironmentLeads data science projects, collaborates with cross-functional teams, and develops predictive modelsAnalyzes data sets, creates reports, and provides insights to support business decisions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprises for strategic data initiativesCommon across various industries for operational and business analysis

The Data Science Lead focuses on leading complex data projects, developing models, and guiding teams, while Data Analysts primarily interpret data, generate reports, and support decision-making. Both roles require strong analytical skills, but the Lead role involves more technical expertise and leadership responsibilities.

What does a data science lead do?

A data science lead oversees data analysis and modeling projects, guiding a team of data scientists to develop insights and solutions using tools like Python, R, and SQL. They coordinate project goals, ensure data quality, and communicate findings to stakeholders, often requiring strong technical skills and leadership abilities.

What are the key skills and qualifications needed to thrive as a Data Science Lead, and why are they important?

To thrive as a Data Science Lead, you need deep expertise in statistical analysis, machine learning, and data modeling, usually supported by an advanced degree in a quantitative field. Familiarity with programming languages like Python or R, experience with data visualization tools (e.g., Tableau, Power BI), and knowledge of cloud platforms (such as AWS or Azure) are typically required. Strong leadership, communication, and project management skills set top candidates apart by enabling them to guide teams and translate complex insights to stakeholders. These skills ensure effective team performance, drive actionable business strategies, and maximize the impact of data-driven initiatives.

What are Data Science Leads?

Data Science Leads are professionals who oversee data science teams and projects within an organization. They are responsible for guiding data-driven strategies, managing data analysts and scientists, and ensuring the successful delivery of analytical solutions. Their role often includes project management, team mentorship, stakeholder communication, and hands-on technical work such as developing models and interpreting data. Data Science Leads bridge the gap between technical data teams and business leaders to drive organizational goals using data insights.

What jobs can data science lead to?

A Data Science Lead can advance to senior roles such as Data Science Director, Chief Data Officer, or Analytics Manager, overseeing teams and strategic initiatives. They often transition into roles requiring leadership, project management, and expertise in machine learning, statistical analysis, and data architecture.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

What is the salary of a lead data scientist?

The salary of a lead data scientist typically ranges from $100,000 to $160,000 annually, depending on experience, location, and industry. Senior roles often include additional compensation such as bonuses, stock options, or benefits, and require strong skills in machine learning, statistical analysis, and programming tools like Python or R.
Infographic showing various Data Science Lead job openings in Virginia as of June 2026, with employment types broken down into 1% As Needed, 89% Full Time, 9% Part Time, and 1% Contract. Highlights an 91% Physical, 4% Hybrid, and 5% Remote job distribution, with an average salary of $144,522 per year, or $69.5 per hour.

Data Science Advisor

Fanniemae

Reston, VA โ€ข On-site

Full-time

Medical, Life

Posted 10 days ago


Job description

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.

Job Description

As a valued contributor to our Internal Audit team, you will serve as a coach, mentor, and subject matter expert, advancing products and initiatives through insights, recommendations, process improvement, automation, and predictive modeling. You will apply expertise in data science, machine learning, AI, large-scale data processing, computational programming, and practical problem solving, while clearly explaining technical solutions to non-technical partners and stakeholders. As an advisor, you will partner across Audit, Technology, Enterprise AI, data science, and risk to architect reusable products on a unified platform that delivers AI-enabled capabilities for stronger risk detection, continuous monitoring, evidence generation, and control-risk reporting. You will also help shape the organization's strategy for applying AI and data science to deliver insights and sound business judgment. In addition, you will provide expert guidance on well-governed models and analytical tools, partnering with senior leadership to advance business and AI transformation and innovation.

THE IMPACT YOU WILL MAKE

The Data Science Advisor role will offer you the flexibility to make each day your own while working alongside people who care so that you can deliver on the following responsibilities:

  • Partner across Audit, Technology, and platform teams to build a unified Audit platform with reusable data, analytics, automation, GenAI services, model operations, secure delivery, and enterprise controls.

  • Develop advanced analytics, AI, and data science solutions to solve complex business and technical challenges and shape technical direction.

  • Design, test, and validate audit solutions using advanced data science methods aligned with audit standards and methodology.

  • Apply data science to improve risk measurement, valuation, decision-making, and business performance.

  • Create technical strategies and executive-ready materials that communicate high-impact solutions to leaders and stakeholders.

  • Provide thought leadership on applying advanced analytics and data science to business challenges.

  • Build solutions for continuous monitoring, risk detection, automated evidence generation, and deeper insights.

  • Assess model effectiveness and fitness for use, ensure testing and monitoring, and explain key drivers and limitations.

  • Lead cross-functional teams through the model lifecycle, aligning changes with business goals.

  • Stay current on industry practices, regulations, and internal standards to ensure compliance and escalate issues as needed.

  • Advise senior leaders on priorities, balancing accuracy, speed, cost, and governance.

  • Support the Model Owner and Lead Model User in building consensus, prioritizing requirements, testing changes, resolving findings, and sharing best practices.

  • Drive continuous improvement in modeling and analytics while promoting accountability, transparency, and proactive model risk management.

  • Represent the Analytics team in internal forums, regulatory settings, and industry conferences, sharing best practices and thought leadership.

THE EXPERIENCE YOU BRING TO THE TEAM

Minimum Required Experiences

  • 6 years of related experience in data science, machine learning, and AI solution development, including GenAI workflows.

  • Master's degree in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field.

  • Advanced proficiency in Python and core data science and machine learning techniques.

  • Experience building end-to-end data science solutions using AWS data services such as Redshift, Athena, S3, and AWS Data Wrangler.

  • Strong analytical skills to support testing, validation, model assessment, and business decision-making.

  • Strong communication skills, including the ability to explain technical concepts and solutions to non-technical partners and stakeholders.

  • Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Desired Experiences

  • PhD in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field, or equivalent additional experience.

  • Experience in Internal Audit, Risk Management, Model Risk Management, or other highly regulated environments.

  • Experience applying advanced data science methods such as regression, SVM (support vector machines), random forests, and neural networks.

  • Strong technical writing, presentation, and executive stakeholder communication skills.

  • Proven ability to influence and collaborate across cross-functional teams, including Audit, Technology, AI, and Risk partners.

  • Experience with AI engineering tools and patterns, such as Anthropic or OpenAI models and tool-calling frameworks.

Internal Audit - Data Science - Advisor

#LI-Hybrid

Qualifications

Education:

Master's Level Degree (Required)

The future is what you make it to be. Discover compelling opportunities at Fanniemae.com/careers.

For most roles, employees are expected to work onsite on a regular basis at their designated office location. In-office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.


Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity/gender expression, marital or parental status, or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment, unless to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process, please complete this form.

The hiring range for this role is set forth below. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being. See more here.

Requisition compensation:

155000

to

209000