An Inside Look at a Principal Associate, Data Scientist Role at Capital One’s Retail Bank Valuations Data Science
Imagining a world where data is at the heart of every decision we make isn’t too far-fetched. In fact, it’s the reality at Capital One, a Fortune 200 company that disrupted the credit card industry by personalizing every credit card offer using statistical modeling and a relational database – a cutting-edge technology back in 1988![source]
Today, Capital One is still leading the charge in data-driven decision-making, using the latest computing and machine learning technologies to unlock big opportunities that help everyday people save money, time, and agony in their financial lives. One of the key teams enabling this transformation is the Marketing & Valuations Data Science Team in the Retail Bank.
The Marketing & Valuations Data Science Team
This team builds models that improve marketing efficiency and drive account growth via intelligent targeting, measurement, segmentation, and customer value modeling. They harness the power of Python and machine learning libraries to manage data and model pipelining, and ensure well-managed model operations. The team thrives on creating best-in-class solutions that provide long-term value in a rapidly evolving space.
The Role of a Principal Associate, Data Scientist
As a Principal Associate, Data Scientist in this team, you’ll be at the forefront of building the next generation of customer valuations models for the Retail Bank. These models are designed to improve marketing efficiency and drive account growth via intelligent targeting, measurement, and segmentation.
The role involves working closely with subject matter experts to deliver flexible, well-managed models that perform well under a variety of economic conditions. You’ll be expected to translate business goals into data science solutions and communicate effectively with senior stakeholders. Part of your responsibilities will also include building machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. Moreover, you’ll get to explore next-generation model architectures (e.g., embeddings, sequence models) to enhance our marketing efficiency.
The Ideal Candidate
Capital One is looking for a candidate who is technically proficient, statistically-minded, creative, and a great storyteller. You should be comfortable with open-source languages and be passionate about further development. Hands-on experience with software engineering techniques and developing end-to-end model pipelines in Python is a must. You should also be experienced in various machine learning algorithms and predictive solutions. Creativity is key as you’ll often be tasked with defining big, undefined problems and pushing hard to find answers. Additionally, effective communication skills are crucial as you’ll need to elucidate technical details to a variety of audiences.
Qualifications
As for qualifications, you should either have or be in the process of obtaining a Bachelor’s Degree in a quantitative field (with at least 5 years of data analytics experience), a Master’s Degree in a quantitative field or an MBA with a quantitative concentration (plus 3 years of data analytics experience), or a PhD in a quantitative field.
Preferred qualifications include a Master’s degree or a PhD in a STEM field, at least 3 years’ experience in Python, machine learning (including XGBoost), and SQL, at least 1 year’s experience in open-source programming languages for large-scale data analysis, and experience with next-generation model architectures such as embeddings, sequence models.
Capital One is committed to creating a diverse, inclusive, and equitable workplace and is willing to consider sponsoring a new qualified applicant for employment authorization for this position.
So, if you’re excited by the prospect of being at the forefront of data-driven decision-making, of using data to unlock big opportunities, and of being part of a team that’s leading the next wave of disruption at a whole new scale, then this role is for you. Learn more about the role Here.
