McLean, VA

Data Jobs in McLean, VA

12 jobs found

Include remote jobs

1d ago

Sr. Associate, Product Manager – Model Analytics & Forecasting

Information Technology Senior Management Forum McLean, VA

McLean, VA

1d ago

$101k - $127k/yr Full time Analytics Data Analytics Financial Analytics

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Job Description

The Sr. Associate, Product Manager for Model Analytics and Forecasting leads product initiatives for model analytics and forecasting within Capital One's Finance Product & Data Solutions, overseeing platforms and governance for analytical models used in Capital Markets risk management.

Responsibilities

Embed with partners and stakeholders across quant model development, balance sheet risk management and Treasury trading desks to understand user pain points and the outcomes expected from modeling tools.
Partner closely with users and end customers, including Quant and Treasury teams, to translate business requirements that enable model development, testing, and deployment.
Collaborate with technology, data and business stakeholder teams, and peers in Research, Design and Architecture to develop and iterate on solutions for high priority needs.
Drive alignment across stakeholders by prioritizing competing initiatives, sequencing development of capabilities and features, and ensuring end-to-end delivery.
Establish success metrics and feedback loops to assess usability, adoption, and impact, iterating based on user and stakeholder feedback.

Requirements

Education: Bachelor’s degree or military experience.
Experience: At least 1 year of product management experience or at least 1 year of experience in product design, agile delivery, business analysis, data science, or software engineering.

Benefits

Health benefits
Financial benefits
Other benefits
Performance-based incentive compensation (cash bonus(es) and/or long term incentives)

Location

McLean, VA (onsite)

Salary

USD 101,100 - 126,900 per year

Salary by Location

Cambridge, MA: $111,200 - $126,900
McLean, VA: $111,200 - $126,900
Richmond, VA: $101,100 - $115,400

Job Type

Full-time

Posted

6/04/2026

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3d ago

Senior Data Analyst

Reithorp Solutions LLC McLean, VA

McLean, VA

3d ago

Full time Senior Analyst Analytics

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Job Description

Based in McLean, VA onsite, Reithorp Solutions LLC offers a Senior Data Analyst role that centers on evaluating IC analytic standards, designing and analyzing surveys, and delivering tailored briefings to senior management. This position emphasizes meaningful impact, collaboration with leadership, and applying advanced data methods to intelligence-related work.

Benefits

401(k) matching
Dental insurance
Health insurance
Life insurance
Vision insurance

Responsibilities

Advise on survey design, testing, and deployment across multiple platforms.
Assist clients in selecting appropriate survey tools across platforms.
Provide expert guidance on methodological aspects to ensure neutrality, accuracy, and repeatability of measures.
Perform cost benefit analyses of survey tools.
Protect respondent anonymity.
Ensure surveys are accessible and accurate by addressing issues before launch.
Oversee survey administration and troubleshoot all technical issues across platforms during the survey window, including accessibility concerns.
Aggregate data and deliver integrated analysis of survey results.
Organize element-specific free text responses and operate AI or LLM tools with multiple prompts to support human review of comments.
Present findings using appropriate visualizations and recommend formats such as scatter charts, donut charts, and stacked column charts to communicate to senior management.
Create customized briefing materials and presentations featuring aggregated data and element-specific data for key stakeholders.

Technologies

LimeSurvey
Tableau
Microsoft Excel
IBM SPSS
AI/LLM tools

Requirements

TS/SCI clearance with Polygraph
BS degree with 8-12 years of prior relevant experience or Masters with 6-10 years of prior relevant experience
Expertise in survey tools and software (for example LimeSurvey)
Experience with survey data analysis methodologies and tools (for example Tableau, Microsoft Excel, IBM SPSS), quantitative methods, and data visualization techniques
Experience advising on intelligence products and processes

Application Question

Do you have a TS/SCI CI Poly Clearance?

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24d ago

Data Engineer - Enterprise, Architecture & Data (EAD) (contract)

Hilton McLean, VA

McLean, VA

24d ago

Contract Analytics AWS Aws Glue

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Job Description

Hilton is seeking a Data Engineer in the Enterprise, Architecture & Data (EAD) group on a contract basis to advance data architecture and enterprise data integration across Hilton’s data ecosystem. The position, based in McLean, VA with a hybrid work arrangement, requires at least three years of relevant experience and a collaborative, cross-functional approach to translating complex requirements into practical data solutions.

Responsibilities

Interpret project requirements to support new and existing systems within the data ecosystem.
Plan and organize work streams, identify data needs, and understand design and solution architectures.
Evaluate enterprise data characteristics and the current technical landscape to gauge implications for new architectures and analytical reporting.
Engage with data and business teams in Martech to align on information assets and gain hands-on experience.
Track projects through the implementation phase and brief senior leadership on status, risks, and issues.
Collaborate with internal partners across Business, Product, Technology, and Analytics functions.
Provide support to internal data teams by clarifying work and proactively addressing risks and issues.
Maintain open communication and alignment across the broader data organization.
Capture detailed requirements for new business initiatives and craft solutions to deliver on these initiatives.

Requirements

Hands-on experience with data quality, ETL, and ongoing data maintenance.
Proficiency in Talend, AWS Glue, and AWS Lambda.
Expertise with CDW and Redshift, Snowflake, and related platforms.
Strong background in cloud and hybrid data environments and platforms.
Familiarity with Amazon Web Services cloud environment.
Ability to function effectively in customer-facing settings.
Solid organizational and project-management capabilities.
Excellent communication and collaboration skills.

Technologies

Talend
AWS Glue
AWS Lambda
CDW
RedShift
Snowflake
AWS
Amazon Web Services

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24d ago

Data Engineer (Bid Role starting in 10 weeks) - TS/SCI w/ Poly

Leading Path Consulting McLean, VA

McLean, VA

24d ago

$175k - $275k/yr Contract Apache Airflow Automation AWS

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Job Description

Leading Path Consulting has a Data Engineer bid role for a planned start in ten weeks. The position is based onsite in McLean, VA, with a salary range of USD 175,000 to 275,000 per year, and a focus on assessing, designing, and implementing robust data infrastructure and pipelines across the organization, emphasizing data quality, observability, and governance. This bid role requires an active TS/SCI with FS poly.

Responsibilities

Conduct comprehensive assessments of current data pipelines, infrastructure, and data flows, including integrations with ServiceNow, network-management tools, and business applications, to identify technical debt, bottlenecks, and reliability issues.
Evaluate current data architecture against industry best practices and organizational needs; develop technical recommendations and a roadmap for data infrastructure improvements.
Design, implement, and maintain production-grade data pipelines using orchestration platforms such as Airflow or Prefect.
Develop resilient ETL and ELT processes from diverse sources including SaaS platforms, network management systems, databases, APIs, files, and streams.
Build API integrations with authentication methods (OAuth, API keys, SSO), plus rate limiting, pagination, retry logic, and error handling.
Extract data from systems not designed for export, reverse-engineering undocumented data structures and relationships.
Manage semi-structured data (JSON and XML) and transform it into structured datasets with consistent schemas.
Design dimensional models, data warehouses, and data marts following industry methodologies.
Create conceptual, logical, and physical data models optimized for query performance and storage efficiency.
Implement slowly changing dimensions and other data warehousing patterns.
Establish naming conventions, data standards, and modeling best practices.
Implement comprehensive data quality checks, validation rules, and automated monitoring with alerting.
Embed error handling, failure recovery, logging, and observability into all processes.
Optimize pipelines for performance, cost, and resource utilization.
Develop reusable components and frameworks; refactor legacy pipelines for reliability.
Build and maintain data infrastructure on cloud platforms (AWS, Azure, or GCP) using infrastructure-as-code with Terraform and CloudFormation.
Implement CI/CD pipelines, version control with Git, and automated testing frameworks.
Manage database performance tuning, indexing, partitioning, and capacity planning.
Establish backup, recovery, security controls, access controls, and compliance measures.
Partner with analysts, software developers, and business stakeholders to translate requirements into technical solutions.
Create comprehensive documentation for systems, processes, and integrations.
Provide technical guidance on data availability and proper usage; enable self-service access.
Troubleshoot pipeline failures, performance issues, and data discrepancies; perform root cause analysis.

Requirements

Active TS/SCI with FS poly required prior to application.
Proven experience building and managing data pipelines.
Hands-on experience with Python.
Experience with cloud computing using AWS services.
Experience processing data with Apache Spark.
Experience with a relational database management system (PostgreSQL, Oracle, MySQL) and writing SQL queries.
Experience working in Linux environments and with shell scripting.
Experience analyzing data in formats such as CSV, XML, JSON, Avro, Parquet, etc.
Experience writing and validating unit tests.

Technologies

Airflow
Prefect
Python
AWS, Azure, GCP
Apache Spark
PostgreSQL
Oracle
MySQL
Linux
Shell scripting
JSON, XML, Avro, Parquet
OAuth, Single Sign-On (SSO)
Terraform, CloudFormation
Git
ServiceNow
NetIM
Forward Networks
Hive
Iceberg
EMR

Benefits

Fully paid medical, dental, and vision premiums
Generous paid time off
11 paid holidays
6% 401(k) contribution
Annual training and tuition reimbursement
SPOT Award bonuses
Regular team events
Opportunities for professional growth and advancement

Travel

Travel is anticipated for this contract, pending sponsor approval. Local travel or point-of-view travel within the local place of performance is expected on an as-needed basis.

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27d ago

Lead Machine Learning Engineer

Capital One McLean, VA

McLean, VA

27d ago

$197k - $225k/yr Full time Artificial Intelligence Azure Ml Cloud Operations

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Job Description

Capital One is seeking a Lead Machine Learning Engineer to drive productionization of ML applications at scale within an Agile team. This onsite role in McLean, VA offers a salary range of USD 197,300 to 225,100 per year and centers on responsible AI, scalable data pipelines, and robust ML infrastructure developed in collaboration with Product and Data Science teams.

Responsibilities

Develop and deploy ML models and components to address real-world business challenges, in partnership with Product and Data Science teams.
Guide ML infrastructure decisions by applying knowledge of modeling techniques and issues, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Tackle complex problems by coding, validating ML models, and implementing automated tests and deployment processes.
Work within a cross-functional Agile team to build and enhance software powering state-of-the-art big data and ML workloads.
Retrain, maintain, and monitor models in production environments.
Leverage or develop cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Design efficient data pipelines to feed ML models.
Apply CI/CD best practices, including automated testing and monitoring, to ensure reliable deployment of ML models and code.
Maintain secure, well-governed code and models, adhering to responsible and explainable AI principles.
Proficient in Python, Scala, or Java.

Requirements

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS
Azure
Google Cloud Platform

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation (cash bonuses and/or long-term incentives)

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27d ago

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)

Capital One McLean, VA

McLean, VA

27d ago

$230k - $262k/yr Full time Deep Learning DevOps Machine Learning

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Job Description

Capital One's Enterprise Platforms Technology (EPTech) team offers a path to productionize machine learning at scale, with a focus on architectural design, development, and governance of ML models and infrastructure. This onsite role in McLean, VA comes with a competitive annual compensation range of USD 229,900 to 262,400, plus a benefits package designed to support health, financial security, and total well-being.

Responsibilities

Design, build, and deliver ML models and components that address real business needs, partnering with Product managers and Data Science teams.
Inform ML infrastructure decisions with a solid understanding of modeling techniques, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias vs. variance, and validation.
Solve complex problems by writing and validating application code, developing ML models, and automating tests and deployment processes.
Collaborate within a cross functional Agile team to create and enhance software that enables state of the art big data and ML applications.
Retrain, maintain, and monitor models once they are in production.
Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Adopt continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code quality and governance to reduce vulnerabilities, maintain risk-aware practices for models, and follow Responsible and Explainable AI principles.
Work with Python, Scala, or Java to implement solutions.

Requirements

Bachelor’s degree; Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a related field.
At least 8 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Scala, or Java.
At least 3 years of experience building, scaling, and optimizing ML systems.
At least 2 years of experience leading teams developing ML solutions.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
3+ years of experience developing performant, resilient, and maintainable code.
3+ years of experience with data gathering and preparation for ML models.
3+ years of people management experience.
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
3+ years of experience building production-ready data pipelines that feed ML models.
Ability to communicate complex technical concepts clearly to a variety of audiences.

Technologies

Python, Scala, Java
scikit-learn, PyTorch, Dask, Spark, TensorFlow
AWS, Azure, Google Cloud Platform

Benefits

Health benefits
Financial benefits
Incentives (cash bonus and/or long-term incentives)
Other benefits that support total well-being

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1mo ago

Lead Machine Learning Engineer (Enterprise Platforms Technology)

Capital One McLean, VA

McLean, VA

1mo ago

$197k - $225k/yr Full time AWS Azure Big Data

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Job Description

This on-site role in McLean, VA focuses on productionizing ML applications and systems at scale within Capital One's Enterprise Platforms Technology group.

Responsibilities

Design, build, and deliver ML models and components that address real world business problems, in collaboration with Product and Data Science teams.
Inform ML infrastructure decisions through understanding of modeling techniques and issues, including model selection, data, feature engineering, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate within a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code is well governed to minimize vulnerabilities, and that models meet risk and Responsible AI / Explainable AI standards.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s Degree.
At least 6 years of experience designing and building data-intensive solutions with distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience designing, scaling, and optimizing ML systems.