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Internship Remote Data Labelling Jobs in Virginia

Imagery Scientist (EO) - Senior

Falls Church, VA · Remote

$97K - $133K/yr

... data standards or to be transformed into a usable state for labeling and model testing purposes ... Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies

Public Health Analyst

Vienna, VA · Remote

$57K - $70K/yr

Remote Alpha Omega is looking for a Public Health Analyst with very strong data management and ... Identify errors/omissions of variable formats or labels. * Document problems and proposed ...

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Internship Remote Data Labelling information

What are the key skills and qualifications needed to thrive as an Internship Remote Data Labelling professional, and why are they important?

To excel as an Internship Remote Data Labelling professional, you need strong attention to detail, basic computer literacy, and familiarity with data annotation processes, often requiring at least a high school diploma or equivalent. Experience with data labelling platforms such as Labelbox or Supervisely, and understanding file formats like CSV or JSON, are commonly expected. Reliability, time management, and effective communication are important soft skills for remote collaboration and meeting deadlines. These competencies ensure high-quality, consistent data labelling that supports accurate machine learning model development.

What is the difference between Internship Remote Data Labelling vs Data Annotation Specialist?

AspectInternship Remote Data LabellingData Annotation Specialist
CredentialsTypically students or entry-level with basic computer skillsOften requires experience or training in data annotation tools
Work EnvironmentRemote, flexible hours, internship settingRemote or on-site, professional setting
Employer & IndustryTech companies, AI startups, research projectsAI, machine learning, data services companies
Search & Comparison IntentLearning opportunity, entry-level roleProfessional data labeling work, career development

Internship Remote Data Labelling typically involves entry-level, temporary roles focused on training and learning, often suitable for students. Data Annotation Specialists are more experienced professionals performing detailed labeling tasks for ongoing projects. While both roles involve data labeling, the internship emphasizes skill development, whereas the specialist role centers on professional expertise.

What are some typical challenges faced by remote data labelling interns, and how can they be addressed?

Remote data labelling interns often encounter challenges such as managing repetitive tasks, maintaining high accuracy, and communicating effectively with team members across different time zones. To address these, it's helpful to establish a structured daily routine, regularly review quality guidelines, and use collaboration tools like Slack or Teams to stay connected. Seeking timely feedback from supervisors and participating in virtual team check-ins can also improve both efficiency and data consistency.

What is an Internship Remote Data Labelling job?

An Internship Remote Data Labelling job involves reviewing and tagging data—such as images, text, or audio—from a remote location to help train machine learning algorithms. Interns in this role classify, annotate, or categorize raw data according to specific guidelines provided by the employer or project. This work is crucial for improving the accuracy of AI models, as properly labeled data enables better learning outcomes. Remote data labelling internships are ideal for students or recent graduates looking to gain experience in AI, data science, or related fields while working from anywhere.
What are the most commonly searched types of Remote Data Labelling jobs in Virginia? The most popular types of Remote Data Labelling jobs in Virginia are:
What cities in Virginia are hiring for Internship Remote Data Labelling jobs? Cities in Virginia with the most Internship Remote Data Labelling job openings:
Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One

Mclean, VA • On-site, Remote

Full-time

Re-posted 11 days ago


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 143 frontline employees who took The Breakroom Quiz

75th of 149 rated banks


Job description

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)
Overview:
At Capital One, we are building the future of financial services by exploring technologies that hold the potential to deliver disruptive change. We're looking for a Senior Manager, Data Science - Quantum Computing Research to work on our fundamental and applied research initiatives in quantum information science. The ideal candidate will have a deep theoretical and practical understanding of quantum computing principles and a proven track record of developing innovative quantum algorithms and applications. This role requires a leader who can not only push the boundaries of scientific knowledge but also translate complex research into tangible, real-world solutions.
This role has a strong strategic aspect and the successful candidate is expected to shape and guide explorations into the application of quantum computing with an emphasis on those applications that are particularly relevant to financial services, including the intersection of quantum computing and AI.
Team Description:
We are looking for a technical leader who has hands-on experience with modern quantum computing technologies. We are committed to pushing the boundaries of scientific knowledge and translating complex research into tangible, real-world solutions that provide a strategic advantage.
As part of the first quantum computing team at Capital One, you will have the opportunity to influence the strategic direction of our quantum computing initiatives. You will collaborate with product, technology, and business leaders to apply the state-of-the-art in quantum computing to financial challenges, and identify promising directions for further exploration. You will be expected to be an external leader, representing Capital One in the research community and collaborating with prominent faculty members in the relevant quantum computing research community.
In this role, you will:
  • Define and execute a research roadmap focused on characterizing the performance of new and emerging quantum algorithms, protocols, and computational methods on tasks and problems that are relevant to financial services.
  • Conduct cutting-edge research in areas such as quantum optimization and quantum machine learning.
  • Collaborate with quantum hardware vendors to co-design algorithms that maximize performance on current and future quantum processors.
  • Publish research findings in top-tier scientific journals and present at international conferences to maintain a strong presence in the quantum community.
  • Identify and evaluate potential business applications for quantum computing, working with internal and external partners to translate research into commercial value as appropriate.
  • Leverage communication skills to convey complex technical concepts to a diverse audience, from fellow researchers to executive leadership.

The Ideal Candidate is:
  • Customer First: You love the process of analyzing and creating but also share our passion for doing the right thing. You know that at the end of the day, it's about making the right decision for our associates and customers.
  • Innovative: You continually research and evaluate emerging quantum technologies. You stay current on published state-of-the-art methods, protocols, and algorithms and seek opportunities to apply them.
  • 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.
  • A Leader: You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
  • Technical: You're comfortable with quantum programming and are passionate about developing further. You have hands-on experience developing quantum algorithms and solutions using open-source tools and quantum cloud computing platforms.
  • Deep Understanding: Has a deep understanding of the foundations of quantum information science and quantum mechanics.
  • Experience: Experience building complex quantum circuits and models, whether for optimization, simulation, or machine learning, as well as expertise in one or more of the following: quantum error correction, quantum complexity theory, or quantum hardware-software co-design.
  • Research Mindset: An engineering mindset as shown by a track record of publications, mentoring junior researchers and interns, partnering with academia, attending conferences, representing Capital One at such research forums, and cultivating relationships with academia while also helping build the talent pipeline.
  • Track Record: A professional with a track record of coming up with new ideas or improving existing ones in quantum computing, demonstrated by accomplishments such as first-author publications or projects.
  • Publications: Has publications in quantum information, physics, computer science, mathematics, or related technical fields.
  • Autonomy: Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

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 7 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 5 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 2 years of experience performing data analytics
  • At least 2 years of experience leveraging open source programming languages for large scale data analysis
  • At least 2 years of experience working with machine learning
  • At least 2 years of experience utilizing relational databases

Preferred Qualifications:
  • Ph.D. in Physics, Computer Science, Mathematics, or a related field with a strong focus on quantum information or quantum computing.
  • At least 7 years of experience in quantum computing research and development.
  • At least 7 years of experience partnering with quantum hardware developers to implement and evaluate algorithms.
  • At least 7 years of experience in quantum algorithms (e.g. Shor's algorithm, Grover's algorithm, Variational Quantum Eigensolver (VQE), and Quantum Approximate Optimization Algorithm (QAOA)).
  • At least 7 years of experience in quantum information theory and quantum computing applied to Machine Learning.
  • Excellent verbal and written communication skills with the ability to effectively communicate technical advances and strategy to research scientists, engineering teams, senior executives, and non-technical audiences.
  • Knowledge of advanced quantum hardware and their associated control systems.
  • Experience with large-scale classical simulation of quantum systems (e.g., with tensor networks or state-vector simulators).
  • Experience with production-level quantum hardware or cloud-based quantum services.
  • Worked with datasets or systems involving 100+ qubits.

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): $209,000 - $238,500 for Sr Mgr, Data Science
McLean, VA: $229,900 - $262,400 for Sr Mgr, 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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