Senior Level Data Science Intern Jobs
Senior level data science intern jobs place experienced practitioners in charge of modeling strategy, end-to-end pipeline ownership, and the cross-functional teams that ship production-ready solutions. Roles are concentrated across Technology & Software, Biotechnology & Pharmaceuticals, and Education, with a mix of on-site, remote, and hybrid settings, and employers like Capital One, Meta, and Amazon hiring at this level now.
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INTRODUCTION
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 Manager, Data Science 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:
As a Data Scientist in the PULSE Business Intelligence team, you will work closely with Pricing, Analytics and Relationship management, product and finance teams to deliver data-driven insights that support strategic business decisions. We focus on transforming complex large data into actionable intelligence that helps optimize pricing strategies, protect and grow revenue, strengthen relationships with partners and improve overall business performance. We are seeking a Data Scientist to support pricing strategy through advanced analytics, predictive modeling.
In this role, you will:
- Partner with a cross-functional team of pricing analysts, finance analysts, data analysts and data engineers to optimize revenue.
- 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:
- 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.
- 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:
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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:
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A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 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 4 years of experience performing data analytics.
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A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics.
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At least 1 year of experience leveraging open source programming languages for large scale data analysis.
- At least 1 year of experience working with machine learning.
- At least 1 year of experience utilizing relational databases.
PREFERRED QUALIFICATIONS:
- PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics.
- At least 1 year of experience working with AWS.
- At least 4 years’ experience in Python, Scala, or R for large scale data analysis.
- At least 4 years’ experience with machine learning and statistical modeling techniques.
- At least 4 years’ experience with SQL.
- Experience with large-scale transaction datasets.
LOCATION
Houston, TX: $179,400 - $204,700 for Mgr, Data Science
This role is Hybrid, with associates expected to consistently spend three days per week in the office.
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.
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. 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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Who's Hiring
- Capital One16

- Meta13

- Amazon10

- Revolution Medicines10

- Adobe7

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- Technology & Software77
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- Education27
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Senior Level Data Science Intern Jobs: Frequently Asked Questions
How do I get a senior level data science intern job?
Employers at this level look for candidates who have led data projects from scoping through deployment, not just contributed to them. A strong portfolio of end-to-end work, experience mentoring junior analysts, and fluency with production ML systems give candidates the clearest edge. Demonstrating that you can set technical direction and communicate findings to non-technical stakeholders is equally important.
Which companies hire senior level data science interns?
Companies hiring senior level data science interns right now include Capital One, Meta, and Amazon, based on current listings on Migrate Mate as of July 2026. Hiring at this level tends to concentrate among organizations with mature data infrastructure, including large technology firms, financial services companies, and research-driven enterprises that need practitioners who can operate independently and guide teams.
Are there remote senior level data science intern jobs?
Yes, remote and hybrid options are widely available at the senior level. About 43% of senior level data science intern openings are remote or hybrid as of July 2026, reflecting how established employers have adapted to distributed technical teams. Senior candidates with strong asynchronous communication skills and experience working across time zones are well-positioned for these roles.
What makes a data science intern role senior level?
A senior level data science intern role is defined by scope, ownership, and influence rather than task execution. Expectations typically include designing modeling approaches, owning data pipelines end-to-end, making architectural decisions, and mentoring earlier-career team members. Senior roles also involve translating ambiguous business problems into technical solutions and presenting findings directly to stakeholders or leadership.
Which industries hire the most senior level data science interns?
Senior level data science intern roles concentrate in Technology & Software, Biotechnology & Pharmaceuticals, and Education, based on current listings on Migrate Mate as of July 2026. These sectors tend to drive hiring at this level because they operate large-scale data environments where senior practitioners are needed to own complex modeling problems, maintain production systems, and develop the analytical capabilities of broader teams.