Data Scientist

• Frame ambiguous revenue-cycle problems as tractable modeling problems and own them end to end such as claim and invoice viability scoring, denial and underpayment prediction, revenue/ARR prediction, and work prioritization from hypothesis to a validated, monitored result in production
• Build and validate models with statistical rigor: thoughtful feature design, sound handling of missingness and class imbalance, calibration, honest evaluation against simple baselines, and a clear treatment of uncertainty
• Design, build, and maintain the data pipelines feeding these models integrating with source collections, billing, and EHR systems and internal data stores, and handling data collection, cleansing, field mapping, and payer/plan normalization with a bias toward reliability and data quality
• Establish and own MLOps practice: model monitoring and drift detection (e.g., population stability), calibration and threshold selection, benchmarking against simple baselines, explainability (e.g., SHAP and interpretable coefficients), experiment and version tracking, and model documentation such as model cards
• Partner with subject-matter experts to encode business-rule and heuristic logic alongside statistical models where that produces a more accurate or more defensible result
• Gather and document business requirements for revenue-cycle initiatives, including workflows, decision points, stakeholder objectives, operational constraints, success criteria, data availability, and underlying business assumptions, and maintain traceability as those requirements evolve.

Senior AI Data Scientist

• Lead advanced machine learning model development, continuous performance monitoring, and ongoing maintenance.
• Oversee model governance and ensure full alignment with internal risk frameworks.
• Serve as the primary lead for handling all related internal audit and OCC regulatory requests.
• Develop business strategies that will drive growth, profitability, and competitive success for Capital One in the face of shifting consumer and regulatory demands.
• May manage and develop 1-2 analysts.
• Develop and implement new product and pricing strategies for various lending products; lead product level modeling/analytics.
• Lead direct-to-consumer marketing efforts for select products, and strategic intent for products distributed through the retail channel.
• Drive step-change improvements in credit performance by connecting drivers of future consumer credit trends to historical behavior, creating risk models, and testing hypotheses using rigorous monitoring and analysis.
• Manage and sequence delivery of business intent, build business requirements and execute against the product strategy.

Business Manager – Modeling and Advanced Data Insights

• Manage project budgets, cost plans, cash flow forecasts, and monthly cost reporting.
• Administer contractor and vendor commercial accounts, including valuations, payment applications, change management, claims, and final accounts.
• Support procurement through tender preparation, bid evaluation, commercial negotiations, and contract administration.
• Develop and maintain project cost plans, benchmarking, value engineering initiatives, and cost optimization strategies.
• Monitor project commitments, risks, accruals, and forecasting to ensure alignment with approved budgets.
• Prepare financial reporting, lender drawdown documentation, and funding support.
• Maintain commercial governance, audit trails, and compliance with project systems, reporting standards, and document management processes.
• Lead commercial aspects of project close-out, including final account reconciliation, benchmarking, audits, and lessons learned.

Senior Cost Manager – Data Center

• Lead the data science services contract team in providing analytical support to address complex business questions and mission needs
• Meet with program leaders, government stakeholders, and technical teams to identify priorities, understand business processes, and guide delivery of innovative data analysis techniques
• Collaborate with data scientists, analysts, engineers, architects, and application developers to support development of data science reports, machine learning models, dashboards, and other analytical solutions
• Assist the team in articulating mission gap problems, process inefficiencies, and operational challenges that can be addressed through data science, business intelligence, or automation
• Oversee implementation of analytical solutions recommended by the team, including data science reports, machine learning models, visualizations, and decision-support products for agency leaders and stakeholders
• Manage project scope, staffing, schedules, risks, deliverables, and performance to ensure contractual obligations are fulfilled and quality standards are met
• Develop, maintain , and communicate work plans, project schedules, roadmaps, backlogs, status reports, and other management artifacts
• Provide expert direction and guidance to subordinate consultants, data scientists, and technical team members
• Serve as the primary point of contact to the Contracting Officer’s Representative and support ongoing coordination with the government Program Manager and other stakeholders
• Manage and control project funds and resources in accordance with contract requirements
• Support Agile delivery activities, including sprint planning, backlog management, prioritization, stakeholder demonstrations, and continuous improvement
• Ensure technical concepts, analytical findings, project risks, and delivery recommendations are communicated clearly to both technical and non-technical audiences
• Support workforce transformation activities by helping teams present data science concepts, analytical products, and lessons learned to large audiences and varied stakeholder groups

Senior Project Manager – Data Science Services

• Partner with a cross-functional team of software engineers, distinguished researchers, and solutions architects to drive great decisions through modeling
• Define and drive towards an end state that is based on simplicity and the adoption of digital technologies, cloud hosting, and open source software.
• Distill the details of complex interconnected modeling systems to influence senior business leaders on model strategy, business use, and risks
• Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners
• Shape our practice of building machine learning models, from design through training, evaluation, validation, and implementation
• Oversee development of benchmark and challenger models to stress test critical modeling decisions

Senior Director, Data Science

• Drive key components of the strategy for the Finance Data Platform team
• Manage the lifecycle of how massive data volumes are sourced and published for Finance consumption
• Collaborate with engineering and data analysts

Manager, Product Management – Finance Data

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Senior Associate, Data Scientist – Bureau Data Strategy

• Conduct data discovery and exploratory data analysis across structured and unstructured data
• Perform data cleansing, normalization, aggregation, and modeling
• Design and build analytic applications in Palantir Foundry, including dashboards and interactive workflows
• Apply advanced analytics and statistical methods such as regression, clustering, hypothesis testing, and A/B testing
• Develop and embed AI/ML capabilities (LLMs, NLP, RAG/GraphRAG) into analytic workflows
• Create clear visualizations and metrics to support executive and operational decision‑making
• Collaborate in an Agile/Scrum environment to rapidly iterate on solutions
• Communicate insights effectively to both technical and non‑technical stakeholders

Data Scientist, Application Developer – Secret Cleared

• Evaluate open-source and internally-developed modeling and analytics tools using real business data
• Integrate internal data with external data sources and APIs to discover and implement actionable insights
• Design and craft data science models to communicate solutions to customers and company leadership

Data Science Internship

Data Science Intern

• Manage strategic relationships with public power partners
• Identify growth opportunities in competitive retail markets and bilateral utility arrangements
• Originate and advance data center infrastructure opportunities with key customers and support customer-facing initiatives
• Participate in the development and delivery of customer proposal presentations
• Coordinate large load registrations, energy management optimization, participate in demand response programs, and develop risk reduction strategies with Structured Trading and Market Operations
• Manage private use networks (PUN) in ERCOT, owning QSE relationships, ensure compliance, and collaborate across teams to optimize energy use for data centers
• Stay up to date on energy regulations, advise on compliance across markets, and build relationships with utilities and regulators in coordination with internal teams
• Support the structuring and execution of retail supply agreements and long-term contracts
• Work with the broader team to prepare internal materials for approvals

Senior Manager, Data Center Infrastructure Origination

Senior Manager, Data Center Infra Origination

• Lead the design, development, and deployment of advanced analytics and AI/ML solutions for mission-critical applications
• Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges
• Deliver innovative, production-ready algorithms and platforms
• Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics
• Work with diverse data types (structured, unstructured, open source, digital media)
• Leverage modern tools such as Python, PyTorch, Scikit-learn, LLM frameworks, and geospatial analytics platforms
• Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast-paced, engineering-centric environment

Senior Data Scientist

• Responsible for mining big data, interpreting and analyzing complex data sets
• Develops and deploys predictive models to analyze company performance and improve customer experiences
• Applies statistical techniques and machine learning algorithms to identify trends within Mazda data
• Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions

• Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity challenges.
• In this role, you will work with our customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products.
• You'll get a chance to work with elite cybersecurity professionals and university faculty to build new technologies that will influence national cybersecurity strategy for decades to come.
• You will co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences.
• Our team works on a wide range of projects. Our current work includes research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems.
• Additionally, we craft metrics and experimental designs for large-scale cybersecurity research programs, develop human-in-the-loop machine learning solutions, and build classifiers to identify security vulnerabilities.

• use advanced statistics, data analytics, machine learning, and artificial intelligence to help government and industry clients research and solve cybersecurity challenges
• work with customers to identify areas where advanced statistical techniques can help tackle problems
• plan and develop prototype solutions and build out final products
• co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences
• engage in research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems
• craft metrics and experimental designs for large-scale cybersecurity research programs
• develop human-in-the-loop machine learning solutions
• build classifiers to identify security vulnerabilities

• Manage project deliverables, including developing scope of work and scheduling project reports
• Manage the development of drawings for clients and property/facility management team
• Proactively manage project-related issues as necessary
• Ensure success in initiation, planning, execution, and completion of all projects against agreed upon targets
• Maintain high qualitative and quantitative standards for work performance
• Prepare agendas and meeting materials, lead meetings, and develop and maintain master project budgets and timelines
• Advise and obtain necessary approvals from management of potential organizational changes
• Coordinate and track all vendor RFQ’s and RFP’s
• Review all change orders and other invoices associated with the project

Project Manager, Project & Development Services – Data Center

• Manage multiple projects on a campus(es) and maintain updated budgets, schedules, and status reports for each
• Create and communicate updates on development program & project status on a monthly basis suitable for executive level reviews
• Effectively present information in a manner to support efficient decision making
• Work with QTS stakeholders, design, and construction teams to create a master development program for site(s), including a complete campus design solution and capital budget
• Manage entitlement and permitting needs for each assigned site project(s)
• Implement and manage multi-phased site development plans to achieve time, budget, and quality standards in a predictable fashion
• Continuously update a campus master plan to provide predictable statistics in a dynamic environment
• Write scopes of work for design, construction, commissioning services & participate in procurement and project cost estimates
• Evaluate and level pricing proposals for design, construction, and commissioning services
• Work closely with strategic procurement team on equipment procurement and delivery process
• Ensure appropriate submittals are coordinated with site stakeholders
• Monitor & create project budget / cost-to-date against overall project budget
• Establish project schedules and manage teams to on-time completion
• Review and approve monthly pay applications from the contractors
• Review change order requests from contractors and negotiate pricing
• Establish site construction security procedures in conjunction with site security team
• Develop plans for product deployment and review / communicate plans with QTS staff involved
• Collaborate with Sales Engineers and Product teams to aid in custom deal solutioning for prospective clients within the applicable schedule and budget for an assigned location
• Establish and maintain relationships serving as liaison with key QTS stakeholders
• Represent QTS Interests as leader in OAC meetings
• Create & build relationships that enhance QTS’s ability to be a leader in creating the World’s Most Valuable Data Center Real Estate
• Aid in due diligence efforts for potential new sites on an as-needed basis
• Work with the internal development team to enhance project management processes and protocols

Development Project Manager – TFO Data Center Construction

• Trusted customer master (the customer lighthouse): a single, governed customer master that includes IDN → member facility → service-line hierarchy, with GPO affiliation (primary and aggregation group), and identifiers integrated with market data
• Fixed, codified metric methodology that serves as one trusted source of truth: a documented, defensible calculation methodology for share-of-wallet, penetration, and addressable/potential value (built on market and GPO data)
• Redefined KPI framework: a smaller, value-based set of leading indicators that measurably changes where RVPs and reps spend their time and holds them accountable to execution
• Initiative tracking linked to EBITDA: a live tracking model where every transformation initiative is linked to its EBITDA impact (calculation owned by Finance) and rolls up to the North Star
• Phase 2 Lighthouse Expansion to the Product Lighthouse: a single, product master data methodology stood up on the same governed model
• Owns: Customer master data methodology and governance: hierarchy logic, GPO affiliation, identity-resolution rules, identifier crosswalks, and integration of market data into the customer lighthouse
• Calculation, methodology, and source of truth for derived commercial metrics (share-of-wallet, penetration, potential/addressable value)
• Design of Commercial KPIs including what is measured, how it is defined, and how it drives focus and accountability
• Initiative tracking model: tracking commercial transformation initiatives and linking each to its EBITDA impact
• The Definitive Healthcare (market-data) relationship, including managing scope changes within an approved budget
• Recommends: Where RVPs and reps should focus from data-driven insights to surface highest value whitespace and penetration opportunities from the trusted data for sales leadership and CVM to act on
• Data, pipeline, and tooling requirements to the ops-data organization focusing on the upstream demand that governs their build
• Sequencing of the lighthouse roadmap (customer → product) and the associated stewardship-ownership decisions
• Informs: Regional and rep-level performance transparency through the redefined KPI set
• Cross-functional and Finance leadership on data-quality gaps, unowned stewardship, and methodology changes that affect reported numbers

Commercial Analytics Lead

• Lead the design and execution of data science projects, ensuring high-impact analytics solutions.
• Partner with client stakeholders to understand business challenges and develop data-driven strategies.
• Oversee data acquisition and integration, ensuring data quality and reliability.
• Apply and refine machine learning and predictive modeling techniques to solve complex business problems.
• Guide the deployment and integration of predictive models into business applications.
• Develop and implement strategies for optimizing model performance and monitoring over time.
• Present findings and recommendations to executives, translating complex data concepts into actionable business strategies.
• Mentor and support junior and senior team members in data science methodologies and best practices.
• Influence data governance and best practices within the organization.

Data Scientist jobs in Virginia

See all jobs on JobTailor

Senior AI Data Scientist

Business Manager – Modeling and Advanced Data Insights

Senior Cost Manager – Data Center

Senior Project Manager – Data Science Services

Senior Director, Data Science

Manager, Product Management – Finance Data

Senior Associate, Data Scientist – Bureau Data Strategy

Data Scientist, Application Developer – Secret Cleared

Data Science Internship

Data Science Intern

Senior Manager, Data Center Infrastructure Origination

Senior Manager, Data Center Infra Origination

Senior Data Scientist

Data Scientist

Senior Data Scientist

Senior Data Scientist

Project Manager, Project & Development Services – Data Center

Development Project Manager – TFO Data Center Construction

Commercial Analytics Lead

Lead Consultant, Data Scientist