Senior Data Scientist

  • 36567
  • Non-Life - Data Science
  • |
  • New Jersey, United States
  • |
  • Jan 10, 2020
Insurance
RESPONSIBILITIES
  • Provide training and mentorship to junior analysts and other coworkers. Structure sessions for the broader community to stay current with industry trends including cutting-edge methodology, software, and platforms while helping evolve best practices.
  • Collaborate and partner with business stakeholders to understand the competitive marketplace, business issues, and data challenges to deliver actionable insights, recommendations and business processes.
  • Continuously advance technological capabilities by automating modeling work, building and deploying new tools and utilizing cutting edge techniques to continually evolve the data science skillset and achieve business objectives.
  • Manipulate high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships, and trends.
  • Perform descriptive and diagnostics analysis to provide actionable insights for a range of business customers via effective visualization.
  • Perform prescriptive analysis seeking for statistical inference providing information that will drive strategic decision making related to marketing, claims and underwriting.
  • Develop predictive models and machine learning solutions to investigate problems, detect patterns and recommend solutions. Work with Information Technology (IT) to integrate the model into production environment.
  • Performs model maintenance and post installation monitoring, including performance tracking, model refit/refresh, documentation, and version control
  • Design best in class sophisticated analytical solutions using advanced data science techniques like Text Mining, Natural Language Processing (NLP), Image Recognition and Robotic Process Automation (RPA)
  • Research and recommend new data, tools, modelling techniques, and vendor solutions to enrich analytics solutions in alignment to policy lifecycle.
QUALIFICATIONS
  • Professional statistics/quantitative skills. Hands-on experience of solving business problem with various multi variate statistical methods including generalized linear model, survival model, time series, mixed effects model etc.
  • Deep understanding and practical experience of applying machine learning techniques and algorithms, such as SVM, GBM etc.
  • Familiar with the whole life-cycle of predictive modeling, including data provision, model development, validation and testing, model deployment.
  • Strong Communication and Presentation Skills in front of diverse audience.
  • Proficient with manipulating data with enterprise-scale database systems (SQL, SAS).
  • Experience with BI tools such as Tableau, Spotfire etc. is required.
  • Hands on experience with Big Data / Hadoop / Spark for 2-3 years is required.
  • Proficient with at least one scripting language such as R, Python, or Java.
  • Experience with version control workflow such as Git is preferred.
  • Experience with web app development is preferred.
  • PhD with 2-3 years of experience, or Masters with 5 years of experience or Bachelors with 7 years of experience and education in Statistics, Economics, Computer Science, Mathematics or related field preferred.
  • At least 5 years of progressive experience in data science, statistical analysis and data modeling.
  • 5 years of experience with statistical software.
  • Insurance industry experience preferred.