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.
Role Summary:
As an ML Scientist at Capital One, you ll be joining 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 arent 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 inform 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 R, Scala, and/or Python.
-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.
-Leader. You challenge conventional thinking and traditional ways of operating and you work with stakeholders to identify and improve the status quo.
Basic Qualifications:
-Master s Degree plus 3 years of experience in machine learning, or PhD
-At least 3 years coding experience with open source programming languages such as Python, R or Scala;
-At least 1 year experience in the application of machine learning to anomaly detection (e.g. density based, outlier detection, unsupervised deep learning)
-At least 1 year experience working with cloud based platforms like AWS or Azure
-At least 1 year experience developing solutions that leverage one or more of the following: operations research, natural language processing, machine learning, deep learning, video/image analysis, or time-series analysis.
Preferred Qualifications:
-PhD in a Machine Learning discipline
-At least 1 year 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 3 years experience developing solutions in Python, Scala, or R-Top-tier peer-reviewed publications on ML research


Associated topics: .net, algorithm, application, c++, java, perl, php, programming, python, software development engineer

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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