Principal Data Scientist
AI summary of the role
Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver a product customers love
What you’ll do
- Leverage a broad stack of technologies — Python, Snowflake, 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
- Work directly with our Enterprise Payments team to streamline all payment/monetary transfer channels, from ingestion through anomaly detection and operational streamlining with agentic processes
What you’ll bring
- Bachelor's Degree in a quantitative field plus 5 years of data analytics experience, or Master's plus 3 years, or PhD
- At least 3 years’ experience in Python
- At least 3 years’ experience with machine learning
- At least 3 years’ experience with SQL
Technologies
Python · Snowflake · AWS · machine learning · neural networks · LLMs · transformer architectures · agentic systems · machine vision · SQL
Source and classification
Internal deployment & tooling · Evidence for this classification:
Description The Bank Operations Data Science team builds the machine learning models that help provide core capabilities internally such as Check/Document Reading, Anomaly Identification, Natural Language Processing of Calls, and operational forecasting. We build ground-breaking industry leading models using emerging technologies like neural networks, LLMs, transformer architectures, and agentic experiences. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver a product customers love Leverage a broad stack of technologies — Python, Snowflake, 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
More from the job description
Principal Data Scientist Principal Associate, Data Scientist - Bank Operations Data Science - Payments Organization 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 Bank Operations Data Science team builds the machine learning models that help provide core capabilities internally such as Check/Document Reading, Anomaly Identification, Natural Language Processing of Calls, and operational forecasting. We build ground-breaking industry leading models using emerging technologies like neural networks, LLMs, transformer architectures, and agentic experiences. Role Description In this role, you will: Partner with a cross-functional team of data scie [... source excerpt omitted ...] 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. 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, Mathemati [... source excerpt omitted ...] ng 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 1 year of experience working with AWS At least 3 years’ experience in Python At least 3 years’ experience with machine learning At least 3 years’ experience with SQL At least one agentic system personally built At least one machine vision model personally built Capital One will
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