Senior Level Data Scientist Jobs
Senior level data scientist jobs put experienced professionals in charge of shaping analytical strategy, owning model outcomes end to end, and guiding the teams and projects that turn data into decisions. Roles are spread across on-site, remote, and hybrid settings in Technology & Software, Banking & Financial Services, and Fintech, with employers like Tiger Analytics, Capital One, and Google hiring at this level now.
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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 BC&P Data Science team enables smarter predictions across the full customer lifecycle for Capital One's Business Cards & Payments products. We build advanced ML solutions — backed by robust data infrastructure and rich behavioral signals — to power decisions at every stage. We work closely with business and technology partners to translate these capabilities into outcomes that serve both business strategy and customer needs.
Role Description:
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.
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.
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
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 9 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 7 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) plus 4 years of experience performing data analytics
At least 4 years of experience leveraging open source programming languages for large scale data analysis
At least 4 years of experience working with machine learning
At least 4 years of experience utilizing relational databases
Preferred Qualifications:
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
At least 1 year of experience working with AWS
At least 3 year of experience managing people
At least 5 years of experience in Python, Scala, or R for large scale data analysis
At least 5 years of experience with machine learning
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: $269,100 - $307,200 for Dir, Data ScienceNew York, NY: $293,600 - $335,100 for Dir, 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.
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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Find JobsSenior Level Data Scientist Job Market
Who's Hiring
- Tiger Analytics16

- Capital One15
- Google12
- JPMorganChase12
- The Home Depot12
Top Industries Hiring
- Technology & Software180
- Banking & Financial Services43
- Fintech29
- Retail24
- Consulting & Professional Services24
Senior Level Data Scientist Jobs: Frequently Asked Questions
How do I get a senior level data scientist job?
Employers at this level look for candidates who have moved beyond executing models to owning the full analytical lifecycle, from framing the problem through to stakeholder communication. A strong portfolio of high-impact projects, experience mentoring junior colleagues, and the ability to translate complex findings into business decisions are what set candidates apart. Depth in a domain, such as NLP, causal inference, or ML systems, also gives applicants a clear edge.
Which companies hire senior level data scientists?
Companies hiring senior level data scientists right now include Tiger Analytics, Capital One, and Google, based on current listings on Migrate Mate as of July 2026. Hiring at this level covers large technology firms, financial institutions, healthcare systems, and data-intensive enterprises that need experienced practitioners to lead projects and drive analytical strategy.
Are there remote senior level data scientist jobs?
Yes, remote and hybrid options are common at this level. About 37% of senior level data scientist openings are remote or hybrid as of July 2026, reflecting how many organizations have structured senior technical roles to support distributed teams. On-site positions do exist, particularly in regulated industries or labs where data access and collaboration require physical presence.
What makes a data scientist role senior level?
Senior level data scientist roles are defined by scope and ownership rather than task execution. Practitioners at this stage set the direction for analytical projects, make independent decisions on methodology, and are accountable for outcomes that affect business strategy. Mentoring junior team members, collaborating cross-functionally with engineering and product, and communicating findings to executive audiences are all standard expectations, not optional additions.
Which industries hire the most senior level data scientists?
Senior level data scientist roles concentrate in Technology & Software, Banking & Financial Services, and Fintech, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they operate on large, complex datasets where experienced practitioners can deliver measurable business impact through advanced modeling, experimentation, and data-informed decision-making.