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Associate Scientist Jobs in Springfield, VA (NOW HIRING)

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

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 ...

Senior Associate, Data Scientist 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 ...

Senior Associate, Data Scientist 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 ...

Principal Associate, Data Scientist

Mclean, VA · On-site

$59K - $60K/yr

Principal Associate, Data Scientist 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 ...

As a Research Associate on the Science and Society team, you'll study how the public understands and experiences science innovations and issues at the center of societal discussion and debate. We ...

Showing results 21-40

Associate Scientist information

See Springfield, VA salary details

$19

$37

$60

How much do associate scientist jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for associate scientist in Springfield, VA is $37.52, according to ZipRecruiter salary data. Most workers in this role earn between $29.13 and $42.69 per hour, depending on experience, location, and employer.

Is an associate scientist entry level?

An associate scientist position is often considered an entry-level or early-career role in research and development, typically requiring a bachelor's or master's degree in a relevant field. It involves performing experiments, data analysis, and supporting scientific projects, with opportunities for skill development and advancement. However, some organizations may require prior experience or specific technical skills depending on the complexity of the work.

What degree do you need to be an associate scientist?

An associate scientist typically needs at least a bachelor's degree in a relevant field such as biology, chemistry, or related sciences. Some positions may require a master's degree or higher, along with laboratory skills and experience with scientific tools and techniques.

What are some common challenges an associate scientist might face when transitioning from academia to industry?

Associate Scientists moving from academia to industry often encounter challenges such as adapting to a faster-paced environment and focusing on project-driven outcomes rather than open-ended research. In industry, there is a stronger emphasis on teamwork, meeting strict deadlines, and following standardized protocols. Adjusting to these expectations, learning new technologies, and effectively communicating results to cross-functional teams are key areas where new hires may need support.

What does an associate scientist do?

An Associate Scientist is a professional who supports research and development projects, typically in fields like biotechnology, pharmaceuticals, or environmental science. They conduct experiments, analyze data, and document results under the supervision of senior scientists. Associate Scientists play a key role in advancing scientific knowledge and product development by performing laboratory tasks, maintaining equipment, and following established protocols. Their work contributes to discoveries, quality control, and regulatory compliance within their organization.

What is an associate scientist?

An associate scientist takes on more responsibilities than an assistant scientist, supporting research and each experiment under the lead scientist, often in a laboratory environment. As an associate scientist, there are many industries you can work in, including the research field where the lead scientist oversees your project, and you help author papers. Many pharmaceutical companies hire associate scientists to analyze samples to develop drugs and assist with preclinical and clinical studies. Private companies need you to produce specialty chemicals for their clients. Materials scientists at the associate level conduct research and test the properties of metals, plastics, and other materials for their use in new products and packaging. Some positions have duties that include training other team members and overseeing students and fellows.

What is the difference between Associate Scientist vs Research Scientist?

AspectAssociate ScientistResearch Scientist
Required CredentialsBachelor's or Master's degree in a relevant field; some roles may require a PhDTypically a Master's or PhD in a related discipline
Work EnvironmentLaboratories, research facilities, industry settingsResearch labs, academic institutions, industry
Employer & Industry UsageBiotech, pharmaceuticals, academia, governmentBiotech, pharmaceuticals, academia, government
Common Search & Comparison IntentUnderstanding entry-level or mid-level research rolesAdvanced research roles, career progression

Associate Scientists and Research Scientists often work in similar environments within biotech, pharma, or academic sectors. The main difference lies in experience and educational requirements, with Research Scientists typically holding higher degrees and engaging in more independent or advanced research. Both roles are essential for scientific progress, but Research Scientists usually have more responsibility and autonomy in their projects.

What are the key skills and qualifications needed to thrive as an associate scientist, and why are they important?

To thrive as an Associate Scientist, you generally need a bachelor’s or master’s degree in a relevant scientific field, along with strong analytical and laboratory skills. Familiarity with laboratory information management systems (LIMS), data analysis software, and standard operating procedures (SOPs) is often required. Attention to detail, problem-solving abilities, and effective teamwork are vital soft skills that distinguish top performers. These skills ensure accurate data collection, reliable experimental outcomes, and productive collaboration within research or product development teams.
What are the most commonly searched types of Scientist jobs in Springfield, VA? The most popular types of Scientist jobs in Springfield, VA are:
What cities near Springfield, VA are hiring for Associate Scientist jobs? Cities near Springfield, VA with the most Associate Scientist job openings:
Infographic showing various Associate Scientist job openings in Springfield, VA as of July 2026, with employment types broken down into 1% As Needed, 55% Full Time, 42% Part Time, 1% Temporary, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $78,050 per year, or $37.5 per hour.

Principal Associate, Data Scientist - Audit Data Science

National Science Teachers Association

Mclean, VA • On-site

$162 - $185/hr

Other

Posted 2 days ago

New


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.

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.

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