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Associate Machine Learning Jobs in Washington, DC

Associate Data Scientist

Arlington, VA

$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 ...

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 25% of the time Minimum Clearance Required: None Clearance Level Must Be Able to Obtain: Public Trust Potential for Remote ...

Associate Data Scientist

Washington, DC

$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 ...

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Associate Machine Learning information

See Washington, DC salary details

$35.7K

$150.7K

$356.2K

How much do associate machine learning jobs pay per year?

As of Jun 8, 2026, the average yearly pay for associate machine learning in Washington, DC is $150,706.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,100.00 and $228,800.00 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, and why are they important?

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 Washington, DC? The most popular types of Machine Learning jobs in Washington, DC are:
What are popular job titles related to Associate Machine Learning jobs in Washington, DC? For Associate Machine Learning jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Associate Machine Learning jobs in Washington, DC look for? The top searched job categories for Associate Machine Learning jobs in Washington, DC are:
Principal Associate, Data Scientist - Mainstreet Acquisitions

Principal Associate, Data Scientist - Mainstreet Acquisitions

Capital One

Mclean, VA • On-site

$59K - $60K/yr

Full-time

Posted 22 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

72nd of 141 rated banks


Job description

Principal Associate, Data Scientist - Mainstreet Acquisitions
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 US Card Intelligence Segments organization builds industry-leading machine learning models that empower core underwriting decisions. We collaborate closely with a wide range of cross-functional partner teams - data engineers, platform engineers, product managers, credit, and business analysts - to deliver solutions from ideation to implementation. The Mainstreet Acquisitions team focuses on acquisitions and retention growth through next level personalization and enhanced decisioning. The associate is responsible for leading a workstream building the next generation of machine learning models used for credit decisioning. These models will be used for critical business decisions, such as card application approve/decline, product optimization, customer valuation, and more.
In this role, you will:
  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
  • Leverage a broad stack of technologies - Python, Conda, AWS, H2O, 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:
  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.
  • 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.
  • 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 with Python
  • At least 3 years of experience with SQL
  • At least 3 years of experience with machine learning
  • At least 3 years of experience in credit risk
  • At least 3 years of experience in financial services

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
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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