Manager, Data Science - Customer Management

Capital One National Association; Chicago (IL); On-site; USD 80,000 - 140,000; Full time

Job summary

An established industry player is seeking a Data Scientist to join their innovative team focused on customer management. In this role, you will leverage cutting-edge technologies to analyze vast datasets and develop machine learning models that enhance customer experiences. Collaborating with a diverse team, you will take ownership of the model lifecycle, from development to deployment. If you are passionate about data and eager to make impactful decisions that benefit customers, this opportunity offers a dynamic environment for your skills to shine. Join a company that values innovation and customer-centric solutions, and help shape the future of financial services.

Qualifications

• 6+ years of experience in data analytics with a quantitative degree.
• Experience with machine learning and open-source programming languages.

Responsibilities

• Partner with cross-functional teams to deliver customer-focused products.
• Build machine learning models from design to implementation.

Skills

Data Analysis

Machine Learning

Statistical Modeling

Interpersonal Skills

Data Retrieval

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field

PhD in a quantitative field

Tools

Python

AWS

H2O

Spark

SQL

Job description

Manager, Data Science - Customer Management

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 Mainstreet Customer Management Data Science team builds industry leading machine learning models to empower various customer management decisions for our existing customers. We collaborate closely with a wide range of cross functional partner teams including software engineers, managers and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - infrastructure and model development, deployment, monitoring, and governance. This team has a primary goal of modernizing machine learning models, making them low-touch with minimal manual features to enhance user experience.

Role Description:

In this role, you will:

1. Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
2. Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
3. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
4. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate is:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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:

1. 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:
1. A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics.
2. 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 plus 4 years of experience performing data analytics.
3. A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics.
2. At least 1 year of experience leveraging open source programming languages for large scale data analysis.
3. At least 1 year of experience working with machine learning.
4. At least 1 year of experience utilizing relational databases.

Preferred Qualifications:

1. PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics.
2. At least 1 year of experience working with AWS.
3. At least 4 years’ experience in Python, Scala, or R for large scale data analysis.
4. At least 4 years’ experience with machine learning.
5. At least 4 years’ experience with SQL.

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

This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.