Sr. Manager Machine Learning Scientist, Anomaly Detection
Mclean, VA

Job Description

77 West Wacker Dr (35012), United States of America, Chicago, Illinois

At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.

Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Sr. Manager Machine Learning Scientist, Anomaly Detection

The Card ML team is working to transform every corner of our business with machine learning. To accomplish this goal, we use the latest techniques in machine learning - deep learning, reinforcement learning, genetic algorithms and natural language processing - and marry them with real-time streaming data in the cloud to create best-in-class enterprise-scale ML products. We tackle a huge variety of business problems and work with vast quantities of data of every kind.

As a Sr. Manager of machine learning at Capital One, you'll be leading a research group that's part of driving 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 difficulty in their financial lives. We do machine learning research and product development differently at Capital One. ML scientists aren't siloed in the lab, but instead partner closely with Software Engineers, Product Managers, and business stakeholders, to discover, invent and build at the largest scale. Ideas may come from internal projects as well as from academic partnerships with world-class institutions. Anomaly detection ML Scientists develop and apply cutting edge and novel approaches to build state-of-the-art fraud prevention and defect identification systems. In this role, you will apply your expertise in anomaly detection and machine learning to guide a research group's agenda and drive critical business outcomes. You stay connected to the wider research community as an active contributor.

The Ideal Candidate will be:

* Technical. You are independent and can develop your own algorithms and experiments. You have hands-on experience developing ML anomaly detection solutions, from concept to production, and selecting the right tool for the job at hand. You understand modern cloud computing. Lots of data do not frighten you, they present a challenge you are eager to take on. You know Python, Scala and/or R.
* Leader. You are an effective mentor, leader, and research group head. Able to guide a team through a cohesive research and execution strategy towards a unified business outcome. You challenge conventional thinking and traditional ways of operating and you work with stakeholders to identify and improve the status quo
* Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art ML methods, technologies and applications. You ask why, explore and openly share your disruptive ideas.
* Business-Minded. You can analyze customer needs and drive towards impactful business outcomes.

Basic Qualifications:

* Master's Degree plus 6 years' experience in machine learning, or PhD plus 3 years' experience in machine learning
* At least 3 years' coding experience with open source programming languages such as Python, Scala or R
* At least 3 years' experience developing solutions that leverage one or more of the following: operations research, natural language processing, machine learning, deep learning, video analysis, image analysis, or time-series analysis.

Preferred Qualifications:

* PhD in a Machine Learning discipline plus 3 years' experience in machine learning
* At least 3 years' experience in the application of machine learning to anomaly detection (e.g. density based, outlier detection, unsupervised deep learning)
* At least 2 years' experience in the application of machine learning to time series anomaly detection
* At least 2 years' experience working with AWS, Azure or similar cloud platform
* At least 5 years' experience developing solutions in Python, Scala or R
* Top-tier peer-reviewed publications on ML research

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