Principal Associate, Data Science
- Richmond, VA
West Creek 2 (12072), United States of America, Richmond, Virginia
Principal Associate, Data Science
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 100 company and a leader in the world of data-driven decision-making.
As a Data Scientist on Capital One's People Analytics team, you'll be part of a mission critical talent system review team providing key insights to stakeholders at the highest levels of the organization. This role offers a unique opportunity to contribute to policy decisions that affect all of Capital One's current and future associates.
You'll be on the leading edge of applying analytics to talent, combining machine learning and social science to build strategies that expand Capital One's talent advantage.
The People Analytics Center of Excellence at Capital One is a 75 person cross-functional team of analysts, consultants, and data scientists. Within People Analytics, the Talent Systems Review team engages with key partners from Human Resources and Legal to build models that help Capital One review processes such as compensation, promotion, and performance. We utilize Python, SQL, AWS, and Tableau to build modular, scalable, statistical models, reporting infrastructure, and dashboards that will provide key insights about our talent systems. Insights will drive decisions at the highest levels of Capital One and will help shape policy impacting our associates.
In this role, you will:
Build models and perform analyses centered on helping Capital One assess our talent systems.
Leverage a broad stack of technologies - Python, AWS, GitHub RedShift, and more
Build predictive models through all phases of development, from design through training, evaluation, validation, and implementation
Writing white papers that explain predictive models you have developed
Flex your interpersonal skills to translate the complexity of your work into tangible insights and policy recommendations
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.
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 backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with regression, clustering, classification, sentiment analysis, time series, NLP and deep learning.
- 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
- 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 1 year experience with NLP
- 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.
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