Principal Associate, Data Scientist Business Data Product

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 youll be part of a team thats 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 Apollo Team is Capital Ones one stop shop for authoritative 360 degree information on US businesses. We are on a mission to build a market leading business critical Business Data Product and Platform that gives our customers a competitive advantage through information. Our customers rely on Apollos data and capabilities to market sell verify underwrite serve and protect business customers often in real-time intelligent ways.

Business data is a complex multi-billion dollar problem that is poorly served by legacy providers. We are tackling this critical opportunity by acquiring and processing massive amounts of data leveraging cutting-edge ML/AI to resolve identity predict valuable features create graph connections to various touchpoints and architecting interfaces that allow our users to seamlessly integrate Apollo into their workflows. Data Science is at the heart of Apollo and this role will have an opportunity to shape the next generation of capabilities.

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:

• 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.

• Technical. Strong background in ML/AI and engineering practices is essential with hands-on experience in areas such as Entity Resolution Information Retrieval Graph-based ML LLMs Embeddings or Deep Learning. Candidates should also be proficient in large-scale data processing using tools like PySpark and be adept at integrating software engineering best practices into their coding.

• Creative. You thrive on bringing definition to big undefined problems. You love asking questions and pushing hard to find answers. Youre not afraid to share a new idea.

• A strong communicator with strong verbal and written communication tailoring the message to the audience including senior leadership audiences

• Results Focused: driven towards results able to drive projects from ideation to prototype to production

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 Bachelors 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 Masters 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:

• Masters 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 PySpark

• 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.

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 candidates 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 theCapital One Careers website. Eligibility varies based on full or part-time status exempt or non-exempt status and management level.

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- or via email at . 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 Ones recruiting process please send an email to

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).