> Markdown version of [/jobs/ext/3055606-principal-data-scientist-ai-for-data-and-assessment](https://www.wearedevelopers.com/jobs/ext/3055606-principal-data-scientist-ai-for-data-and-assessment). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Scientist - AI for Data and Assessment - **Company:** Capital One Financial Corporation - **Location:** San Jose, CA, United States - **Salary:** $161,800.0 - $184,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Standard Sql, Sentiment Analysis, Cloud Platform System, Apache Spark, Deep Learning, Information Technology, Data Analytics - **Published:** September 24, 2026 - **Apply:** https://www.capitalonecareers.com/job/mclean/principal-data-scientist-ai-for-data-and-assessment/1732/101007328000 ## About the Role * 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. * Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. * Statistically-minded. You've built models, validated them, and back tested 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., * 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, 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), * 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, SQL * At least 3 years' experience with Deep Learning Frameworks * At least 3 years' experience with Natural Language Processing ## Description The AI for Data team builds and ships state of the art machine learning solutions to support data lifecycle within the enterprise. We partner with product, tech and design teams to deliver personalized experiences to our data and platform users to drive productivity and innovation. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging ML technologies. 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 ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Got AI ideas but no money? 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