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Machine Learning Scientist 1330 views

At Capital One, they’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 their customers succeed by bringing ingenuity, simplicity, and humanity to banking. They measure their efforts by the success their customers enjoy and the advocacy they exhibit.

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

Machine Learning Scientist

At Capital One, data is at the center of everything they do. When they launched as a startup they 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 their passion for data have skyrocketed them to a Fortune 200 company and a leader in the world of data-driven decision-making.

Department Summary

The Card ML team is working to transform every corner of their business with machine learning. To accomplish this goal, they 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. They tackle a huge variety of business problems and work with vast quantities of data of every kind.

On Any Given Day You’ll Be

  • Using Big Data tools (Hadoop, Spark, H2O, AWS) to conduct 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
  • Building machine learning models from development through testing and validation to their 30+ million customers in production
  • Designing rich data visualizations to communicate complex ideas to customers or company leaders
  • Investigating the impact of new technologies on the future of digital banking and the financial world of tomorrow

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.

Twenty-five years after Capital One was started it’s still led by its founder. Be ready to join a community of the smartest people you’ve ever met, who see the customer first, and want to use their data skills to make a difference.

Basic Qualifications

  • Master’s Degree
  • At least 2 years of coding experience with open source programming languages (e.g. R, Python, or Scala)
  • 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 analysis, image analysis, or time-series analysis.

Preferred Qualifications

  • Ph.D. in a Machine Learning discipline
  • At least 2 years of experience in machine learning
  • At least 1 year of experience working with AWS, Azure, or similar cloud platform
  • At least 2 years of 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.

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