Manager, Data Scientist

Capital One • McLean, VA

1d • $179,400 - $245,600

About The Position

Manager, Data Scientist Manager, Data Scientist, Card Credit Innovation 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 Card Credit Innovation team under US Card builds cutting-edge models and infrastructure for financial analysis that informs lending decisions for ~100 million Capital One customers. We are developing a generative AI-based solution for data analysis, code generation, document synthesis, and recommendation to drive efficiency in our business and data analytics teams. You will work with an experienced team of product managers, engineers, data scientists, and business analysts to experiment with emerging technologies in generative AI and deliver software implementing these technologies. 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 Fine-tune and customize large language models across text and vision modalities for use in financial data analysis Manage large scale data annotation projects by guiding business analysts to curate high quality datasets, delivering model improvements by driving improvements to data collection processes Collaborate with software engineers to develop, deploy, optimize, and maintain data and model pipelines Leverage a broad stack of technologies — Python, PyTorch, Hugging Face, Dask, LangChain, and more — to reveal the insights hidden within huge volumes of numeric and textual data 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. 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 backtested 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.

Requirements

• 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 A 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

Nice To Haves

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
• At least 2 years’ experience fine-tuning and deploying transformer based models using deep learning libraries and tools such as Pytorch and HuggingFace
• At least 2 years’ experience working with unstructured data for natural language processing, computer vision or speech applications
• At least 4 years’ experience in Python, SQL for large scale data analysis
• At least 4 years’ experience with machine learning

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Fine-tune and customize large language models across text and vision modalities for use in financial data analysis
• Manage large scale data annotation projects by guiding business analysts to curate high quality datasets, delivering model improvements by driving improvements to data collection processes
• Collaborate with software engineers to develop, deploy, optimize, and maintain data and model pipelines
• Leverage a broad stack of technologies — Python, PyTorch, Hugging Face, Dask, LangChain, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

What This Job Offers

• Job Type: Full-time
• Career Level: Manager