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Data Science Training Jobs in Virginia (NOW HIRING)

Data Science SME Lead

Fort Belvoir, VA · On-site

$120K - $189K/yr

Data Science SME Lead TULK supports U.S. national security customers with cleared experts who ... Deliver GEOINT tradecraft learning in classroom, virtual, and mobile training environments. * Help ...

As a part of the Data Science team you'll have opportunities to work on projects that expand your ... Training or fine-tuning LLMs * Experience with Machine Learning, including * * Feature selection ...

As a part of the Data Science team you'll have opportunities to work on projects that expand your ... Training or fine-tuning LLMs * Experience with Machine Learning, including * * Feature selection ...

As a part of the Data Science team you'll have opportunities to work on projects that expand your ... Training or fine-tuning LLMs * Experience with Machine Learning, including * * Feature selection ...

Showing results 21-40

Data Science Training information

See Virginia salary details

$23.8K

$101.1K

$189.6K

How much do data science training jobs pay per year?

As of Aug 20, 2026, the average yearly pay for data science training in Virginia is $101,124.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,049.00 and $119,621.00 per year, depending on experience, location, and employer.

What is data science training?

A Data Science Training job involves teaching and guiding individuals or teams in data science concepts, tools, and techniques. Trainers design curricula, conduct workshops, and provide hands-on experience with programming languages like Python or R, machine learning, and data visualization. They may work for educational institutions, corporate training programs, or independently to upskill professionals. The goal is to equip learners with the skills needed to analyze data, build models, and make data-driven decisions.

What are the typical responsibilities of a professional in data science training?

Individuals in Data Science Training roles are responsible for developing, organizing, and delivering curriculum on topics such as data analysis, machine learning, and data visualization. They often lead workshops, create interactive tutorials, and provide one-on-one guidance to learners from diverse backgrounds. Collaboration with data science teams and subject matter experts to ensure training content is current and industry-relevant is common. Additionally, professionals assess learner progress and adapt materials to continuously improve the educational experience. This role is ideal for those passionate about teaching and staying at the forefront of new data science advancements.

What are the key skills and qualifications needed to thrive in data science training, and why are they important?

To excel in Data Science Training roles, you need a solid foundation in data analysis, statistical modeling, and expertise with programming languages like Python or R, often supported by a degree in data science or a related field. Familiarity with tools such as Jupyter Notebooks, SQL, machine learning platforms, and certifications like Google Data Analytics or Microsoft Certified: Data Scientist Associate are highly valued. Excellent communication, patience, and instructional skills help convey complex topics clearly and foster a collaborative learning environment. These combined skills are essential for effectively designing and delivering training that empowers learners to succeed in the rapidly evolving field of data science.

How do I get a job in data science training with no experience?

To get a job in data science training with no experience, focus on building foundational knowledge through online courses, certifications, and practical projects. Developing strong communication skills and familiarity with tools like Python, R, or SQL can also improve your chances, and gaining experience through internships or volunteering can help demonstrate your abilities to employers.

What training do you need to be a data science training?

To become a data science trainer, you typically need a strong background in data science, including skills in programming languages like Python or R, statistical analysis, and machine learning. Relevant certifications, such as Certified Data Scientist or specialized training programs, can enhance credibility, and experience with data tools and platforms is often required. Continuous learning and staying updated with industry trends are also important for effective training.

What are the most commonly searched types of Data Science Training jobs in Virginia?

The most popular types of Data Science Training jobs in Virginia are:

What are popular job titles related to Data Science Training jobs in Virginia?

For Data Science Training jobs in Virginia, the most frequently searched job titles are:

Infographic showing various Data Science Training job openings in Virginia as of August 2026, with employment types broken down into 62% Full Time, 18% Part Time, 4% Temporary, and 16% Contract. Highlights an 96% In-person, and 4% Remote job distribution, with an average salary of $101,124 per year, or $48.6 per hour.

Principal Associate, Data Scientist - Audit Data Science

Capital One

Mclean, VA • On-site

$59K - $60K/yr

Full-time

Re-posted 11 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

93rd of 171 rated banks


Job description

Principal Associate, Data Scientist - Audit Data Science
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 Scientist 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.
Team Description
Innovation is at the heart of everything we do on the Audit Insights and Innovation team. We're not a traditional Data Science team: we build creative ML solutions across multiple domains, such as LLM based chatbots, GenAI powered applications, AML/Fraud identification, and Customer call transcripts intelligence. Opportunities to learn and build fast allow our team members to develop towards their full potential. We partner closely with product, tech, and design teams to enable faster build-to-market cycles for product features that delight our customers with dynamic and integrated experiences.
You will be the driving force to experiment, innovate, and create next-generation features powered by the latest emerging NLP and Generative AI technologies. If you love a fast-paced, highly rewarding environment, and you love being a builder and communicator, this is the place for you.
In this role, you will:
  • Partner with a cross-functional team of data scientists, data analysts, risk professionals, software engineers, and product managers to manage the risk and uncertainty inherent in statistical models in order to lead Capital One to the best decisions
  • Leverage a broad stack of technologies - Python, Conda, UV, AWS, 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

The Ideal Candidate is:
  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out 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.
  • 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.
  • An LLM practitioner. You have hands-on experience building with open-source LLM models to create reproducible, production-grade pipelines. You leverage AI-assisted development tools like Claude Code to accelerate prototype development, moving quickly from idea to working solution.
  • Collaboration and Communication. You're capable of effectively articulating data insights and analytics strategies to a diverse audience, including auditors, engineers, product managers and leadership.
  • Statistically-minded. You've built models, validated them, and back tested 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.
  • A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

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 5 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 3 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)

Preferred Qualifications:
  • Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)
  • At least 3 years of experience in Python, Scala, or R
  • At least 3 years of experience with machine learning
  • At least 3 years of experience with SQL
  • At least 1 year of experience working with AWS

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.
McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science
Richmond, VA: $147,100 - $167,900 for Princ Associate, 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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