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 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 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 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.
-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.
-- Master s Degree plus 6 years of experience in data analytics, or PhD plus 4 years of experience in data analytics
-At least 4 years experience in open source programming languages for large scale data analysis and modeling
-At least 4 years 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.
-PhD in a Machine Learning discipline plus 5 years of experience in machine learning
-At least 5 years experience in Machine Learning with focus on Time Series/Forecasting
-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
- At least 3 years of experience mentoring junior data scientists and providing technical governance and oversight
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