Manager, Data Science

Capital One Group; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One seeks a Manager, Data Science to lead data-driven projects across billions of customer records, applying ML and statistical techniques in a cloud-based environment. You will collaborate with data scientists, engineers, and product managers to deliver customer-centric analytics products.

You will work with Python, AWS, H2O, Spark and PyTorch, driving model development from concept to production and communicating results to non-technical stakeholders.

Qualifications

• Bachelor's, Master's, or PhD in a quantitative field or related MBA with quantitative concentration
• Experience with open source tools and modern cloud computing platforms
• Experience with machine learning and working with large-scale data analytics

Responsibilities

• Partner with cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage Python, AWS, H2O, Spark to analyze large datasets and extract insights
• Build ML models from design through training, evaluation, validation and implementation
• Translate complex technical work into tangible business goals

Skills

Python

AWS

Spark

H2O

Conda

Machine Learning

Open Source Tools

Education

Bachelor's degree in a quantitative field

Master's degree in a quantitative field or MBA with quantitative concentration

PhD in a quantitative field

Tools

PyTorch

DASK

PySpark

Kubeflow

Job description

Manager, 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.

The Card DS team is working continuously to innovate the way we handle data to transform every corner of our business through analytics, infrastructure, valuations, and strategy. We build human-centric experiences for moments that matter throughout the customer journey, and we do this by harnessing data, technology, and talent to propel our business forward. To accomplish this goal, we design, build, and maintain the appropriate solutions we use across Card to make smart, informed decisions.

We use the latest techniques in machine learning to build predictive models and utilize the advantages of large-scale data and cloud-based processing. Through these techniques, we extract relevant insights from data to tackle a huge variety of business problems.

Responsibilities

• 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

Ideal Candidate

• Curious and creative. You thrive on bringing definition to big, undefined problems. You love asking questions, and you love pushing hard to find the answers. You’re not afraid to share a new idea. You communicate clearly and effectively to share your findings with non-technical audiences.
• Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms. You are not afraid of petabytes of data.
• Statistically-minded. You have 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 analysis and deep learning.
• Customer and product oriented. You share our passion for changing banking for good.

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 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
• 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
• 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
• 3+ years of hands‑on experience building, deploying, and maintaining high-scale, production-grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines
• Deep expertise (4+ years) in developing and optimizing state‑of‑the‑art Deep Learning models, specifically Transformer‑based architectures, using PyTorch and distributed training with multi‑GPU optimization
• Extensive experience (4+ years) with high‑performance, distributed data processing for petabyte‑scale feature engineering using frameworks like DASK and PySpark

Salary and Benefits

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: $197,300 - $225,100

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.

Equal Opportunity / Diversity

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 [e-mail]. 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 [e-mail].

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).

At Capital One, we’re building a leading information-based technology company. Still founder‑led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit.