Principal Associate, Data Scientist - Business Data Product

Capital One • McLean, VA

18d

About The Position

Principal Associate, Data Scientist - Business Data Product 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 Apollo Team is Capital One’s one stop shop for authoritative, 360 degree information on US businesses. We are on a mission to build a market leading, business critical Business Data Product and Platform that gives our customers a competitive advantage through information. Our customers rely on Apollo’s data and capabilities to market, sell, verify, underwrite, serve, and protect business customers, often in real-time intelligent ways. Business data is a complex, multi-billion dollar problem that is poorly served by legacy providers. We are tackling this critical opportunity by acquiring and processing massive amounts of data, leveraging cutting-edge ML/AI to resolve identity, predict valuable features, create graph connections to various touchpoints, and architecting interfaces that allow our users to seamlessly integrate Apollo into their workflows. Data Science is at the heart of Apollo and this role will have an opportunity to shape the next generation of capabilities. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love 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 Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals 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. Technical. Strong background in ML/AI and engineering practices is essential, with hands-on experience in areas such as Entity Resolution, Information Retrieval, Graph-based ML, LLMs, Embeddings, or Deep Learning. Candidates should also be proficient in large-scale data processing using tools like PySpark and be adept at integrating software engineering best practices into their coding. 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. A strong communicator with strong verbal and written communication, tailoring the message to the audience, including senior leadership audiences Results Focused: driven towards results, able to drive projects from ideation to prototype to production

Requirements

• 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 5 years of experience performing data analytics 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 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Nice To Haves

• 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 3 years of experience in Python, Scala, or R
• At least 3 years of experience with machine learning
• At least 3 years of experience with SQL, PySpark
• At least 1 year of experience working with AWS

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• 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
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level