Locations: VA - Richmond, United States of America, Richmond, Virginia
Overview
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 Marketing & Valuations Data Science Team in the Retail Bank builds models that improve marketing efficiency and drive account growth via intelligent targeting, measurement, segmentation, and customer value modeling. If you enjoy the challenge of creating best-in-class solutions that provide long term value in rapidly changing space, this is the role for you.
Role Description
In this role you will
- Partner with a cross-functional team of data scientists, business analysts, software engineers, and product managers to deliver a product customers love
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Leverage a broad stack of technologies — Python, Kubeflow, Spark, 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
- 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.
- 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.
Basic Qualifications:
- Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date
- At least 1 year experience in open source programming languages for large scale data analysis
- At least 1 year experience with machine learning
- At least 1 year 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)
- 3+ years’ experience in open source programming languages for large scale data analysis
- 3+ years’ experience with machine learning
- 3+ years’ experience with relational databases
- 3+ years’ experience with SQL
- Experience with Kubeflow Pipelines
- Experience with XGBoost
#J-18808-Ljbffr