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Remote Director Machine Learning Jobs in Virginia

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

At least three (3) years of direct experience in machine learning. * Must have a Advanced Degree ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

At least three (3) years of direct experience in machine learning. * Must have a Advanced Degree ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Comcast

Engineer 6, Machine Learning, Data & AI

Reston, VA · On-site +1

$119K - $143K/yr

... remote option.) Job Summary We are seeking a visionary Senior Technologist, Data & Agentic AI ... Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.

Maximus

Data Scientist (Remote)

VA · On-site +1

General information Job Posting Title Data Scientist (Remote) Date Tuesday, August 4, 2026 City ... NLP, and machine learning (both supervised and unsupervised) to improve relevance and ...

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Remote Director Machine Learning information

What does a remote director of machine learning do?

A Remote Director of Machine Learning leads teams of data scientists and engineers to develop, implement, and oversee machine learning solutions for an organization, all while working remotely. They are responsible for setting the strategic direction for ML projects, collaborating with stakeholders, and ensuring that models align with business objectives. This role typically involves both technical leadership—such as reviewing algorithms and architectures—and managerial duties, such as mentoring staff and managing budgets. Working remotely, they use digital collaboration tools to communicate, monitor progress, and deliver results effectively.

How does a remote director of machine learning typically coordinate and lead distributed teams across different time zones?

As a Remote Director of Machine Learning, effective coordination of distributed teams requires strong communication strategies, including regular video meetings, clear documentation, and use of collaborative project management tools. Leaders in this role often establish overlapping core hours and leverage asynchronous communication to accommodate various time zones. They focus on aligning goals, fostering a culture of transparency, and ensuring continuous progress through well-defined milestones. Building trust and maintaining team engagement remotely are common challenges, but successful directors prioritize mentorship, feedback, and virtual team-building activities to create a cohesive work environment.

What are the key skills and qualifications needed to thrive as a remote director of machine learning, and why are they important?

To thrive as a Remote Director of Machine Learning, you need advanced expertise in machine learning algorithms, data science, and leadership, typically supported by a graduate degree in a related field and extensive experience in deploying ML solutions. Familiarity with tools like Python, TensorFlow, PyTorch, cloud platforms, and experience with project management systems is essential, and certifications such as AWS Certified Machine Learning can be advantageous. Outstanding communication, strategic thinking, and the ability to mentor and manage distributed teams are crucial soft skills in this role. These skills and qualities are vital to successfully lead innovative ML projects, align technical teams with business goals, and drive impactful outcomes in a remote environment.

What is the difference between Remote Director Machine Learning vs Remote Data Science Manager?

AspectRemote Director Machine LearningRemote Data Science Manager
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related field; experience in ML algorithmsMaster's in Data Science, Statistics, or related; strong analytical background
Work EnvironmentLeads ML teams, develops models, and oversees deployment in tech-focused companiesManages data science teams, focuses on insights and analytics for business decisions
Employer & Industry UsageTech firms, AI startups, large enterprises with AI initiativesFinancial, healthcare, retail, and other industries leveraging data insights

While both roles require advanced education and involve data-driven work, the Remote Director Machine Learning primarily focuses on leading ML model development and deployment, whereas the Remote Data Science Manager emphasizes managing data analysis teams and deriving business insights.

What are the most commonly searched types of Remote Machine Learning jobs in Virginia?

The most popular types of Remote Machine Learning jobs in Virginia are:

What are popular job titles related to Remote Director Machine Learning jobs in Virginia?

For Remote Director Machine Learning jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Director Machine Learning jobs in Virginia look for?

The top searched job categories for Remote Director Machine Learning jobs in Virginia are:

What cities in Virginia are hiring for Remote Director Machine Learning jobs?

Cities in Virginia with the most Remote Director Machine Learning job openings:

Remote Director Machine Learning jobs near you

Senior Director, Data Science (Remote-Eligible)

Capital One

Mclean, VA • On-site, Remote

Full-time

Posted 29 days ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

92nd of 171 rated banks

Job description

Senior Director, Data Science (Remote-Eligible)
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Science Leader at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
The Intelligent Foundations and Experiences (IFX) group is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering. The Emerging AI Patterns team within IFX group is a new strategic initiative to explore and operationalize cutting-edge AI paradigms like Agentic frameworks, multi-agent collaboration. We are specifically focused on revolutionizing how Capital One develops, deploys, and manages a large number of machine learning models through Agentic AI systems.
In this role, you will:
  • 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

The Ideal Candidate is:
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
  • Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

Basic Qualifications:
  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date :
    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 11 years of experience performing data analytics
    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 9 years of experience performing data analytics
    • A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
  • At least 6 years of experience leveraging open source programming languages for large scale data analysis
  • At least 6 years of experience working with machine learning
  • At least 6 years of experience utilizing relational databases

Preferred Qualifications:
  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
  • At least 6 years of experience in Python, Scala, or R for large scale data analysis
  • At least 6 years of experience with machine learning
  • At least 2 year of experience working with AWS
  • At least 6 years of experience with complex architectural patterns (SOA), building APIs, microservices, and event streams
  • At least 6 years of experience with DevOps or DevSecOps and building CI/CD pipelines using Jenkins, Artifactory, Chef, Ansible, AWS CloudFormation templates, GitHub, and Sonar

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is open to hiring a Remote Employee for this opportunity.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Remote (Regardless of Location): $286,200 - $326,700 for Sr Dir, Data Science
McLean, VA: $314,800 - $359,300 for Sr Dir, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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