Senior Associate, Data Scientist - Marketing Analytics

11 West 19th Street (22008), United States of America, New York, New York

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 Marketing Analytics team generates insights that drive all marketing efforts in the small business space with the objective of deepening relationships with our existing customers and winning new customers. There are a number of areas where we are looking to leverage the power of data science. We want to build sophisticated machine learning models to better understand which prospects or existing customers we should reach out to and in what channels and at what frequency, models to assess customer value and personalize treatments. 

We work with a number of partner teams to ensure that the models drive business value and can be used in decision making and in marketing campaigns.

Role Description

In this role, you will:

• build machine learning models through all phases of development, from design through training, validation, and deployment

• help our business leaders make better 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 and product managers to deliver a product customers love

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

The Ideal Candidate:

• 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:

• Bachelor’s Degree plus 2 years of experience in data analytics, or Master’s Degree, 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 or PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Physics or related disciplines.

• At least 2 years of experience with Python or R, SQL and scripting

• At least 2 years of experience working with and analyzing large datasets

• At least 2 years of experience building, analyzing and deploying machine learning models

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that