Senior Manager of Data Science for Machine Learning, Conversational AI 824 views

Job Description

Location: Vienna, VA

Capital One is seeking a Data Scientist for an exciting initiative to develop multichannel natural language intelligent assistants that provide an outstanding experience for our customers.  So far we’ve brought to life Eno, Capital One’s intelligent assistant, and our Alexa and Cortana skills. We’re quickly improving these and adding more channels. You will work closely with our product, design, and tech teams to develop machine learning models leveraging rich data to bring greater intelligence and humanity to our conversational AI.

At Capital One, data is at the center of everything we do. When we were a tiny 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 that 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.

Twenty-five years after Capital One was started it’s still led by its founder who is committed to making it a leading tech company, not just a leading bank. Be ready to join a community of the smartest people you’ve ever met, who put the customer first, and want to use their data skills to change banking for good.

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 distributed computing technologies and operating across billions and billions of customer transactions to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.  You’ll also be part of a strong community of hundreds of data scientists doing industry-leading work.

In this position you’ll spend time:

• Writing code, probably Python, to create machine learning models from development through testing and validation, then working with tech teams to deploy to our 30+ million customers in production
• Leading a small team of data scientists focused on building and deploying models
• Building partnerships with other ML teams to help deliver more, faster, better
• Mapping whitespace. You’ll have a lot of latitude to create your own research agenda while focusing on where your team can provide the best value.

On any given day, you might find yourself:

• Collaborating with our AI teams to make Eno ever smarter
• Brainstorming with our Design teams to dream up the next cool way to make Eno more empathetic
• Using Tensorflow and/or other hot tools for building robust, deployable models
• Using Spark and related tools to manage the analysis of billions of customer transaction records
• Writing software to clean and investigate large, messy data sets of numerical and textual data
• Integrating with external data sources and APIs to discover interesting trends (NOAA Weather Data + Credit Card Transactions = Fascinating!)
• Designing a rich data visualization to communicate complex ideas to customers or company leaders
• Investigating the impact of new technologies on the future of mobile banking and the financial world of tomorrow
• Reading up on a new modeling algorithm that the industry is starting to use

The ideal candidate will be a…

• Strong communicator, able to respectfully explain complex ideas and project influence to a diverse, collaborative audience.
• Constructive skeptic, able to internalize the wisdom of the community, but also can see where changing facts require new ideas and is not afraid to say so.
• Quick learner, able to master new tools and modeling techniques in order to effectively challenge decisions made by fast-moving partners
• Data wrangler. You know how to programmatically extract data from a database and an API, bring it through a transformation or two, and model it into human-readable form (ROC curve, map, d3 visualization, Tableau, etc.).
• Results-focused modeler. You are a passionate expert in Machine Learning theory and execution, but you also know that a model’s value emerges from a complex interaction of theory, people, data, and processes.

Basic Qualifications:

• Bachelor’s Degree plus 6 years of experience in data analytics, or Master’s Degree plus 4 years of experience in data analytics, or PhD plus 2 years of experience in data analytics
• 3+ years experience in open source programming languages for large scale data analysis
• 3+ years experience with machine learning
• 3+ years experience with relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 2 years of experience in data analytics
• 2+ years experience working with Cloud environments
• 1+ year experience managing people
• 5+ years experience in Python, Scala, R, or other modern programming language
• 7+ years experience with statistics or machine learning

2+ years experience with Natural Language Understanding models