Senior Data Scientist

  • 39032
  • Non-Life - Data Science
  • |
  • Texas, United States
  • |
  • Feb 3, 2021
Insurance
RESPONSIBILITIES
  • Deliver start to finish on projects leveraging large spectrum of different types of data
  • Design, build, and validate models using modeling techniques that may include advanced AI and Deep Learning solutions
  • Work with key business leaders, underwriters, actuaries, or other necessary departments to receive needed data, assumptions, requirements, deliverable format, and prior project work
  • Lead cross-functional project teams to build project road maps, establish deadlines, and implement models
  • Develop a high-level understanding of cutting-edge data science tools and techniques
  • Establish and promote best practices by applying leadership and problem-solving skills
  • Build collaborative relationships across the organization
QUALIFICATIONS
  • PhD or Masters in quantitative discipline, such as statistics, data science, computer science, mathematics, engineering, physics, etc. with preference to having proven work experience in NLP, Deep Learning, or AI
  • Proven experience interacting with non-technical business managers to identify opportunities to apply predictive analytics to business opportunities
  • Proven experience managing multiple projects simultaneously
  • Manage a full project life cycle and implementation
  • Developing a non-managerial collaborative environment
  • Possess and have ability to apply basic knowledge of principles, practices, and procedures
  • Excellent written and verbal communication, facilitation, and coaching skills in a business context and as it applies to team and project management with an emphasis on confidentiality, tact, and diplomacy.
  • Good organizational and analytical skills; demonstrated ability to manage multiple tasks simultaneously.
  • Knowledgeable of industry changes, legal updates and technical developments related to applicable area of the Company’s business to proactively respond to changing business environment.
  • Strong Working experience with analytical modeling tools such as R or Python, predictive modeling, machine learning, experimental design, NLP, and deep learning related technologies
  • Demonstrated leadership competencies, including teambuilding, creative problem-solving, flexibility, and willingness to challenge the status quo