Data Science Python Developer

Key Skills

Python Programming, SQL, Big Data Technology, Machine learning techniques, Large scale data processing

Job Description

Data Science Python Developer

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

Our team is building key infrastructure to enable the data community in US Card to easily create, share, and reuse metrics critical to building models and making good credit decisions. We sit at the intersection of Python, SQL, and the business, with a heavy technical focus. Our product is in the early stages of development, with a small but highly-skilled team and growing adoption from users. We follow software engineering best practices with robust testing and automation, but also carefully design our products to have elegant and intuitive user experiences. Our core tech stack is Python, Snowflake, Conda, and Jenkins, and we also use Jupyter Notebooks and shell scripts.

Role Description

You’ll be designing, writing, or reviewing code the majority of the time, but because the team is small and our products are still under heavy development you’ll also be able to have an important voice in our strategic direction.

Success in this role looks like:

• One month: Initial onboarding completed, beginner understanding of the team’s vision and codebase, able to do small code reviews and contribute small well-defined features.
• Three months: intermediate understanding of our vision and codebase, regularly performing code reviews and adding medium-size features, providing user support.
• Six months: expert-level understanding of our codebase, able to add larger and less well-defined features.
• One year: expert-level understanding of our vision, influencing technical and product direction of the project.

In this role, you will:

• Develop robust Python-based tools with an emphasis on technical design and code quality
• Engage with the data science, data analyst, and business analyst community to learn about their data challenges and translate those needs into new software capabilities
• Explore the cutting edge of metrics design, architecture, and testing
• Be on the ground floor of an emerging product, with many opportunities to define the direction and vision for the team

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.
• 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:

• 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

Preferred Qualifications:

• At least 3 years’ experience in Python
• At least 2 years’ experience with SQL
• At least 1 years’ experience building business metrics from tabular data
• Any prior experience building software tools for other people to use

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