Principal Associate Data Scientist, Retail Bank

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Principal Associate Data Scientist, Retail Bank

Capital One is a diversified bank that offers a broad array of financial products and services to consumers, small business and commercial clients. Ranked #127 on the Fortune 500, Capital One has one of the most widely recognized brands in America. As one of the nation’s top 10 banks, we offer a broad spectrum of financial products and services to consumers, small businesses and commercial clients. We nurture a work environment where people with a variety of thoughts, ideas and backgrounds, guided by our shared Values, come together to make Capital One a great company and a great place to work.

At Capital One, data is at the center of everything we do. When we launched 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.

Team Description:

This role offers a a unique opportunity to be part of a dynamic analytics and modeling team focused on developing behavior models for balance sheet portfolios. We are currently looking for candidates with strong modeling and analytical skills. This position will work with other quantitative analysts, data scientists, and the business analysts in developing and enhancing the deposit modeling framework to support multiple business purposes in Capital One.

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

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• 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.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. Your passionate about talent development for your own team and beyond.
• 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 phase 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.

Basic Qualifications:

• Bachelor’s Degree plus 5 years of experience in data analytics, or Master’s Degree plus 3 years in data analytics, or PhD
• At least 1 year of experience in open source programming languages for large scale data analysis
• At least 1 year of experience with machine learning
• At least 1 year of experience with relational databases

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)
• Experience in Optimization ortime-series modeling techniques
• At least 1 year of experience working with AWS
• At least 3 years’ experience in Python, Scala, or R
• At least 3 years’ experience with machine learning
• At least 3 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.