1

Data Science Product Manager Jobs in Washington (NOW HIRING)

... the success of product and initiative workstreams through insights, product and change ... Experience in Internal Audit, Risk Management, Model Risk Management, or other highly regulated ...

... production-grade solutions • 3-6 years Experience leading teams, projects, or functional ... Proven ability to develop managers and senior ICs, coach technical and leadership growth, and ...

Data Science SME

Quantico, VA · On-site

$119K - $133K/yr

As a Data Science Subject Matter Expert with JCTM you will provide technical expertise and ... data management. * Experience developing data pipelines analytical workflows and repeatable ...

Build / manage production-ready data science product lifecycles, continuous delivery and automation pipelines (MLOps), orchestration / model management in cloud environment; cluster large amount of ...

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists and researchers to build products. We are looking for ex.

Senior Data Architect

Washington, DC · On-site

$76.25 - $102/hr

Partner with data science, product, and engineering leadership. * QUALIFICATIONS : * 8+ years in data engineering/architecture, 3+ as an architect. * Deep expertise in AWS, Azure, or Google Cloud ...

Showing results 41-60

Data Science Product Manager information

See Washington salary details

$58.3K

$180.5K

$223.1K

How much do data science product manager jobs pay per year?

As of Aug 18, 2026, the average yearly pay for data science product manager in Washington is $180,541.00, according to ZipRecruiter salary data. Most workers in this role earn between $159,700.00 and $223,100.00 per year, depending on experience, location, and employer.

What is a Data Science Product Manager?

A Data Science Product Manager is a professional who bridges the gap between data science teams and business objectives by guiding the development of data-driven products. They work closely with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure successful product delivery. Their role involves understanding both the technical aspects of machine learning and analytics as well as user needs and business strategy. This ensures that data-powered products are effective, user-focused, and aligned with organizational goals.

How does a Data Science Product Manager typically collaborate with data scientists and engineers during a product lifecycle?

A Data Science Product Manager plays a crucial role in bridging the gap between business objectives and technical teams. Throughout the product lifecycle, they work closely with data scientists to define project goals, prioritize features, and translate business needs into actionable data-driven solutions. They also coordinate with engineers to ensure the seamless integration of machine learning models into products, address technical constraints, and facilitate communication between cross-functional teams. This collaborative approach ensures that data science initiatives are both technically feasible and aligned with overall business strategy.

What are the key skills and qualifications needed to thrive as a Data Science Product Manager, and why are they important?

To thrive as a Data Science Product Manager, you need a strong background in product management, data analytics, and a foundational understanding of machine learning, often supported by a degree in a technical or quantitative field. Familiarity with tools like SQL, Python, JIRA, and knowledge of data platforms and agile methodologies is typically required. Excellent communication, strategic thinking, and the ability to bridge technical and non-technical teams are vital soft skills. These competencies ensure successful product development, effective stakeholder alignment, and the delivery of impactful data-driven solutions.

What is the difference between Data Science Product Manager vs Data Analyst?

AspectData Science Product ManagerData Analyst
Required credentialsBackground in data science, product management, or related fields; often requires experience with machine learning and data-driven product developmentTypically holds a degree in statistics, mathematics, or business; skills in data visualization and basic analytics
Work environmentCollaborates with product teams, data scientists, engineers; focuses on developing data products and strategiesWorks with business units to interpret data, generate reports, and support decision-making
Employer and industry usageUsed in tech companies, e-commerce, and organizations developing data-driven productsCommon across finance, marketing, healthcare, and business intelligence roles

The main difference is that Data Science Product Managers oversee the development of data products and strategies, requiring a blend of product management and data science skills. Data Analysts focus on interpreting data and generating insights to support business decisions. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are popular job titles related to Data Science Product Manager jobs in Washington?

For Data Science Product Manager jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Data Science Product Manager jobs in Washington look for?

The top searched job categories for Data Science Product Manager jobs in Washington are:

What cities in Washington are hiring for Data Science Product Manager jobs?

Cities in Washington with the most Data Science Product Manager job openings:

Infographic showing various Data Science Product Manager job openings in Washington as of August 2026, with employment types broken down into 84% Full Time, 9% Part Time, 2% Temporary, and 5% Contract. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution, with an average salary of $180,541 per year, or $86.8 per hour.

Principal Associate, Data Scientist - Audit Data Science

Capital One

Mclean, VA

$59K - $60K/yr

Full-time

Re-posted 9 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

92nd 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 theCapital 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).


What Capital One employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom