Capital One is looking to leverage data science and machine learning to manage risk and uncertainty, leading to better decisions. The Audit Analytics and Innovation team specifically aims to build creative ML solutions for domains like LLM chatbots, GenAI applications, AML/Fraud identification, and customer call transcript intelligence, enabling faster build-to-market cycles for customer-delighting features.
Requirements
- At least 2 years of experience with machine learning with a focus on Natural Language Processing
- At least 2 years of experience working with Natural Language Processing models (e.g., Transformers)
- At least 2 years of experience in Python, Scala, Dask, Spark or R for large scale data analysis
- At least 2 years of experience with SQL
- At least 1 year of experience working with AWS
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Experience with clustering, classification, sentiment analysis, time series, and deep learning.
Responsibilities
- Partner with a cross-functional team of data scientists, data analysts, risk professionals, software engineers, and product managers to manage risk and uncertainty in order to lead Capital One to the best decisions, not just avoid the worst ones
- Leverage a broad stack of technologies (Python, Conda, Flask, Dash, Hugging Face, LangChain, AWS, H2O, Spark, and more) to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning and NLP models through all phases of development, from design through training, evaluation, validation, and implementation.
- Productionize highly scalable data pipelines for faster feature changes and updates, and implementing data validation framework and quality tests
- Develop visualization tools to streamline model monitoring reports
- Investigate new technology to advance data management, model development and deployment and drive change in enterprise ML products
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Other
- 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.
- 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.
- You’re capable of effectively articulating data insights and analytics strategies to a diverse audience, including auditors, engineers, product managers and leadership.
- You’ve built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve.
- “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.
