Data Scientist

  • 36894
  • Non-Life - Data Science
  • |
  • North Carolina, United States
  • |
  • Feb 25, 2020
Insurance
RESPONSIBILITIES
  • Research current processes and proactively identify emerging needs for analytic models.
  • Develop supervised and unsupervised models and dashboards.
  • Evolve and advance a customer behavioural segmentation model, building marketing, sales and product predicative models, analyzing results and movements of segments/clusters and providing business insights to grow the company’s market share and revenue.
  • Design, create and implement advanced analytics and forecasting models to optimize business processes.
  • Provide insights for decision making through the use of ML, traditional statistical modeling and BI.
  • Perform monthly reporting of some key metrics as a part of advanced business intelligence support to functional areas.
  • Partner with IT and Enterprise Data Management Organization teams on the evaluation of data assets and their proper use.
  • Become a trusted analytical partner to the functional areas of support and collaborate on the development and planning of analytic projects in response to business needs.
  • Develop and perform preliminary exploratory analysis on datasets associated with building advanced ML models. Ability to work with structured and unstructured data.
QUALIFICATIONS
  • Bachelor’s degree required.
  • 4+ years business analytics and business support functions experience.
  • 4+ years of experience in one or more of the following statistical / analytic languages such as Python, Apache Spark, Hive, and Scala in a cloud computing environment.
  • 4+ years of experience in one or more of the following: database query and management tools.
  • Hands-on experience with advanced analytics like logistic regression, time series, forecasting, optimization, and other predictive modeling techniques. ML experience and knowledge of ML platforms, libraries and programming.
  • Hands-on experience working with advanced BI tools, dashboard experience with visualization and automation tools, Tableau experience preferred.
  • AWS Certification or proven experience in a cloud computing environment such as, Databricks, Azure, Cloudera, Hortonworks, Google Cloud, Anaconda etc.
  • Some experience with legacy analytics software such SAS or willingness to learn the basics.
  • Ability to translate business needs into technical requirements and articulate analytic solution to get business buy-in.
  • Ability to influence decision makers and drive consensus.
  • Master’s or PhD in a quantitative research field.
  • Experience or background in customer focused fields including marketing, sales, customer research and product management.
  • Ability to perform complex day-to-day ETL tasks such as data gathering, data cleaning, wrangling, coding or programming, business and analytics requirements gathering, and data analysis.
  • Experience with large analysis datasets and enterprise scale database systems.