Digital Data Scientist

Company Name: JPMorgan Chase
Location: New York, NY
Date Posted: 26th Apr, 2016
  • The ideal candidate has deep skills in one or more areas mentioned below, and is passionate about solving real-world problems. We are looking for those select few who thrive in a dynamic environment, have big ideas and goals, and believe in testing ideas rather than talking about them.
  • They are hands-on, without needing an army of engineers or other data scientists to support them, and love learning new skills along the way. They feel comfortable working with a diverse team of UX designers, product managers, business leaders and engineers. 
  • You will be joining one of the most elite data science teams on Wall Street: several of us have worked at other software companies and start-ups before joining the team.
  • You are passionate about changing the financial lives of millions of people by making banking simple, personal and human, and by using data, algorithms and insights.
  • Strong background in statistics, modeling and optimization as demonstrated by either industry experience or coursework/academic research.  Participation in KDD and Kaggle competitions will be a big plus.
  • MS/PhD in a quantitative discipline such as Statistics, Physics, Economics, Applied Math, Computer Science, Operations Research, or Computational Sciences, with coursework and projects in machine learning and data analysis.  Publications in top machine learning, AI or data science conferences and journals are highly desirable. 
  • 5+ years experience with Apache Hadoop and Spark ecosystems of open-source tools and ML packages. Our data processing and modeling pipelines are built using Spark, MapReduce, Hive, Kafka, ElasticSearch, HBase, Cassandra, and other open-source platforms.  Our team develops the platforms that analyze petabytes of data, develop  attributes and deploy models to production - efficient implementation and elegant architecture is essential.
  • Solid understanding of algorithms to build recommendation systems, interest graphs, ad targeting models, trend analysis, and fraud/anomaly detection using online and offline features. A big part of the role is to be able to ask open-ended questions, explore new ideas, and choose appropriate techniques for solving a given problem, rather than using packages as a black box to a known problem.
  • Must be able to write clean and concise code in at least two of the following: Python, Java, and Scala. Our interview process includes writing some code to solve a problem on the whiteboard.