Senior Associate, Data Science

Senior Associate, Data Science

Senior Associate, Data Scientist -  Marketing Analytics

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 Business Cards Marketing Data Science is a team of talented data scientists leveraging cutting-edge machine learning models and statistical methods to deeply understand customer behavior, so we can optimize our marketing campaigns to win new customers and drive sticky relationships with our existing customers. 

In the recent past, we have experimented with multiple modeling approaches including time-series models, regression & classification models, ensemble models, LLMs, causal learners to name a few. Our objective is to drive model usage across every aspect of marketing and increase personalization. 

We are embedded within the teams owning the campaigns and hence work very closely with business analysts and marketers to ensure that the models drive business value and are used in decision making and in marketing campaigns.

Role Description

In this role, you will:

• build machine learning models end-to-end, from ideation through training, validation, and deployment

• influence our business leaders to make better data-driven decisions by conducting rigorous statistical analyses of various business strategies

• partner with a cross-functional team of data scientists, data engineers, software engineers, business analysts, marketers and product managers to deliver a product customers love

• leverage a broad stack of technologies — Python, SQL, Cloud services and more — to build and monitor models and deliver transformational insights from data

 

The Ideal Candidate is:

• is technical. You have hands-on experience developing data science solutions using open-source packages. You’re comfortable with Python, SQL, command line, AWS, etc. and are passionate about developing these skill sets further. You are able to write well documented and efficient code that is production-grade and that your team can leverage. You know how to work with messy data sources. 

• is statistically-minded. You understand statistical concepts like sampling, bias, uncertainty, etc. and can reason using these principles. You know how to interpret the outputs of standard statistical models. You have experience with hypothesis testing, regression models, classification models and clustering. 

• has strong written and verbal communication skills. Your documentation clearly articulates your thinking and you can communicate results well to your peers and other technical and business leaders. 

• is a self-starter and a creative problem solver. You take initiative, iterate quickly and know how to move past challenges. You address business problems using actionable analyses and data science solutions. 

Basic Qualifications:

• 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 2 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

Preferred Qualifications: