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Associate Machine Learning Jobs in Ashburn, 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 ...

Associate Data Scientist

Washington, DC · On-site

$66K - $67K/yr

Training machine learning models to solve complex problems. * Productionizing models in a Scala ... Associate Data Scientist position on our Data Science team. The Data Science team works closely ...

Associate Data Scientist

Washington, DC · On-site

$66K - $67K/yr

Training machine learning models to solve complex problems. * Productionizing models in a Scala ... Associate Data Scientist position on our Data Science team. The Data Science team works closely ...

Showing results 21-40

Associate Machine Learning information

See Ashburn, VA salary details

$32.2K

$136.1K

$321.6K

How much do associate machine learning jobs pay per year?

As of Aug 10, 2026, the average yearly pay for associate machine learning in Ashburn, VA is $136,070.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,000.00 and $206,600.00 per year, depending on experience, location, and employer.

What is the difference between Associate Machine Learning vs Data Scientist?

AspectAssociate Machine LearningData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in CS, Statistics, or related; often requires experience with data analysis and programming
Work EnvironmentEntry-level, team-based projects, focused on supporting ML models and data preprocessingMore autonomous, involved in data analysis, model development, and interpretation
Employer & Industry UsageTech companies, startups, research labs; roles in AI and ML teamsWide range of industries including tech, finance, healthcare, and consulting

While both roles involve working with data and machine learning, an Associate Machine Learning typically focuses on supporting ML projects with less experience, whereas a Data Scientist has broader responsibilities including data analysis, model development, and strategic insights. The roles often overlap but differ in scope and experience level.

What are the key skills and qualifications needed to thrive as an associate machine learning engineer?

To thrive as an Associate Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, usually supported by a relevant degree. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience with data processing libraries and version control systems is typically required. Strong analytical thinking, problem-solving ability, and effective collaboration skills help you stand out in this role. These competencies are essential for developing robust models, working efficiently with teams, and delivering impactful data-driven solutions.

What are some common challenges faced by associate machine learning professionals when transitioning from academic projects to real-world business applications?

Associate Machine Learning professionals often find that moving from academic or theoretical projects to business-focused environments introduces new challenges. Real-world datasets can be messy, incomplete, or imbalanced, requiring additional data cleaning and preprocessing. Moreover, business timelines may require rapid prototyping and iterative model development, which is different from the more open-ended nature of academic research. Collaborating with cross-functional teams such as data engineers, product managers, and business stakeholders is also essential to align models with organizational goals. Adapting to these practical aspects is key to succeeding in an Associate Machine Learning role.

What does an associate machine learning engineer do?

An Associate Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the supervision of senior engineers. They handle tasks such as data preprocessing, model evaluation, and maintaining machine learning pipelines. Associates often collaborate with data scientists, software engineers, and business teams to ensure that machine learning solutions are integrated effectively into products or services. This role is typically entry-level or early career and is a stepping stone toward more advanced machine learning positions.
What are the most commonly searched types of Machine Learning jobs in Ashburn, VA? The most popular types of Machine Learning jobs in Ashburn, VA are:
What job categories do people searching Associate Machine Learning jobs in Ashburn, VA look for? The top searched job categories for Associate Machine Learning jobs in Ashburn, VA are:
What cities near Ashburn, VA are hiring for Associate Machine Learning jobs? Cities near Ashburn, VA with the most Associate Machine Learning job openings:

Principal Associate, Data Scientist - Retail Bank Marketing

Capital One

Mclean, VA • On-site

$59K - $60K/yr

Full-time

Re-posted 26 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

93rd of 170 rated banks


Job description

Principal Associate, Data Scientist - Retail Bank Marketing
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
The marketing data science team in the Retail Bank builds the machine learning models that make our marketing more efficient: how much to spend on each digital marketing channel, the optimal product and channel to market each customer, and the estimated value of new accounts. We do data and model pipelining, machine learning, and well-managed model operations using Python and ML libraries in our tech stacks. If you enjoy the challenge of creating best-in-class solutions that provide long term value in a rapidly changing space, this is the role for you.
Role Description
In this role, you will:
  • Work closely with subject matter experts to deliver flexible, well managed models that perform well under a variety of economic conditions
  • Translate business goals into data science solutions and communicate with senior stakeholders
  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  • Explore next-generation model architectures (e.g. embeddings, sequence models) to unlock value in our marketing efficiency

The Ideal Candidate is:
  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience with software engineering techniques and developing end to end model pipelines in Python.
  • Statistically-minded. You are experienced in various machine learning algorithms and predictive solutions
  • 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 storyteller. You are effective in communicating technical details to a variety of audiences

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' experience in Python
  • At least 3 years' experience with machine learning
  • At least 3 years' experience with SQL

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
New York, NY: $176,500 - $201,400 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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