Senior Associate, Data Science - People Analytics

West Creek 2 (12072), United States of America, Richmond, Virginia

Senior Associate, Data Science - People Analytics

As a Data Scientist on Capital One’s People Strategy & Analytics team, you’ll be on the leading edge of applying analytics to talent, combining machine learning and social science to build models that seek to understand associate behavior, and inform strategies aimed at expanding Capital One’s talent advantage.

Role Description

A data scientist on the People Strategy & Analytics team is responsible for designing and delivering modeling, as well as research and analysis in support of Capital One’s talent agenda, which includes a wide range of topics such as:

• Attracting, developing, and retaining top talent

• Ensuring a phenomenal associate experience

• Building a high performing, highly diverse executive pipeline

• Maximizing productivity

• Rethinking how we measure talent

Human capital problems require particular attention to sample size impacts, covariance, selection bias, modeling choices, and other issues that can be the difference between highly meaningful & impactful results, and noise.  In this role, you will leverage structured problem solving approaches and data science skills to identify and deliver high impact solutions, as well as develop unique data science skills and human-capital expertise.

The Ideal Candidate is:

• Passionate about human capital: You are excited by the value we can add to our company and our associates, and are inspired to help make a large positive impact

• 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 clustering, classification, sentiment analysis, time series, and deep learning.

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 in data analytic

• 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 

• 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)

• At least 1 year of experience working with AWS

• At least 2 years’ experience in Python, PyTorch, Scala, or R

• At least 2 years’ experience with machine learning

• At least 2 years’ experience with SQL

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

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

Salaries for part-time roles will be prorated based upon the agreed upon