Job Directory Senior Machine Learning Scientist

Senior Machine Learning Scientist
San Francisco, CA

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Job Description

201 Third Street (61049), United States of America, San Francisco, California

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.

Senior Machine Learning Scientist

At Capital One, data is at the center of everything we do. When we launched as a 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 this 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.

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.

On any given day you'll:

* Use Big Data tools (Spark, H2O, AWS) to conduct the analysis of billions of customer transaction records
* Lead the full cycle of iterative exploratory data analysis, including hypothesis formulation, algorithm development, data structuring, testing, insight generation/visualization, and action planning
* Apply proven machine learning methods and hacking skills in working with open-source and proprietary technologies to explore and extrapolate insights from divergent data types
* Independently collaborate with peers, data engineers, database managers, and business analysts across multiple businesses in designing and implementing research and development strategies and communication of insights for complex and unique business problems
* Investigating the impact of new technologies on the future of digital banking and the financial world of tomorrow

The Ideal Candidate will be:

* Curious. You ask why, you explore, you're not afraid to blurt out your disruptive idea. You probably know Python, Scala, or R and you're constantly exploring new open source tools.
* 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.).
* Creative. Big, undefined problems and petabytes of data don't frighten you. You're used to working with abstract data, and you love discovering new narratives in unmined territories.

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 plus 1 year of experience in Data Science, or PhD
* At least 3 years of experience in machine learning algorithms using Python (Pandas, NumPy, SciPy, Scikit-Learn, TensorFlow, and pyTorch, etc.)
* At least 2 years of experience working with relational databases and SQL
* Exceptional troubleshooting and problem-solving abilities
* At least 1 year experience working with AWS and Big Data solutions such as Spark

Preferred Qualifications:

* PhD degree in Statistics, Computer Science, Mathematics, Physics, or related technical field with a strong publication record or demonstrable record of delivery
* Experience deploying machine learning algorithms to a production environment
* Experience in time series analysis and forecasting
* Experience developing machine learning algorithms for one or more of the following: Natural Language Processing, Deep learning, Hidden Markov Models, Reinforcement Learning, Contextual Multi-armed Bandit, Bayesian modeling

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

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