Senior Data Scientist

  • 37169
  • Non-Life - Data Science
  • |
  • Missouri, United States
  • |
  • Apr 7, 2020
Insurance
RESPONSIBILITIES
  • Meet with stakeholders to identify high-level project requirements and formulate timelines, milestones, and tasks as part of project execution.
  • Provide status reports to management regarding project progress.
  • Translate business requirements, for a given project, into novel technological solutions.
  • Work alone, or in collaboration with team members, to design, develop, and implement predictive models that meet business needs, that integrate into existing business processes, and that deliver sound predictions and/or analytical output.
  • Continuously explore data, data structures, modeling techniques, algorithms, software, and testing methodologies to ensure use of best practices in modeling efforts.
  • Assist with quality assurance testing of data, analytical output, and predictive models.
  • Work with internal and external customers to further the adoption and utilization of the company predictive models.
QUALIFICATIONS
  • Advanced degree in computer science, mathematics, statistics, engineering, physics or other sciences.
  • 4 to 7 years of experience in related fields.
  • Education should include significant work in advanced mathematics, statistics, and/or data science. Undergraduate or graduate work in computer science is a plus.
  • Possesses an intense curiosity and determination to explore and solve complex business problems utilizing data, technology, and analytical techniques.
  • Thorough understanding of project management practices and approaches including waterfall and Agile methodologies. Experience with project management software such as Microsoft Team Foundation Server or JIRA.
  • Experience with a variety of modeling techniques including, but not limited to, Decision Trees, Naïve Bayes methods, Clustering, Regression, Neural Networks, Support Vector Machines, Markov Processes, and ensemble methods utilizing both structured and unstructured data.
  • Experience building and deploying deep learning models in a business setting.
  • Thorough understanding of procedures for training, testing and validating predictive models.
  • Advanced understanding of Databases and the SQL Language - SQL Server / Oracle / MySQL.
  • Programming languages - C++, C#, Java, Python, etc.
  • Experience with operating systems including Microsoft Windows and UNIX.
  • Experience with big data solutions such as Hadoop and its ecosystem.
  • Understanding of containerization software such as Docker.
  • Experience with code management techniques utilizing tools such as Microsoft Team Foundation Server, Github, etc.
  • Excellent listening and interpersonal skills.
  • Experience working in a team-oriented, collaborative environment.
  • Ability to translate very complex subject matter into understandable written and oral communications.