Data Science Co- Op/Internship

Key Skills

Bayesian networks, Data science techniques, Decision trees, Effective communication skills, Linear Models, Machine learning techniques, Multivariate analysis, Non Linear Programming, Python Programming, R Programming, SAS, Software Development, SQL

Job Description

This position will be critical in advancing our mission to drive profit-focused technical excellence and innovation within the Plymouth Rock Group of Companies. The position will be responsible for research and development of new predictive models and new analytical techniques around insurance pure premiums, customer life time value, customer buying behaviors and other related topics utilizing internal and external data. This work will be used in setting pricing, underwriting and product strategies for the Plymouth Rock group of Companies. The analysis and modeling will be tested via implementation both broadly and on a pilot basis to allow us to learn and refine our approaches in rapid succession.

Data Analysis:

The Data Science Intern will work with internal and external data to understand key drivers of expected insurance losses and lifetime customer value. This will require that the Intern acquires an understanding of various internal and external data sources, is able to illicit hypothesis from internal personnel regarding key variables and test those hypotheses using available data.

Modeling:

The Data Science Intern will help develop and enhance models used in a variety of contexts within the product management structure of Plymouth Rock. The Intern will be responsible for advancing the modeling capabilities within Plymouth Rock and transferring those advancements to other product management personnel.

Implementation:

The Data Science Intern will work with the product community to facilitate the application of models developed considering the regulatory and competitive contexts within which we operate. This will include ensuring that models are well understood, the implications are appropriately assessed, implementation plans are defined, validation of results are undertaken and adjustments are made rapidly.

Qualifications:

• Graduate Student from a doctoral program in the areas of economics, statistics or a related field (background in Bayesian statistics preferred).
• Practical experience in Econometrics and Statistics, preferably in a business context.
• Strong written and oral communication skills and an ability to communicate technical concepts to both technical and non-technical audiences.
• High standards for the work products delivered.
• Creative thinker with the ability to synthesize information from various sources and apply that information to concrete business problems.
• Flexibility and resiliency characteristic of a professional.
• Knowledge of, and experience with, the technical aspects of insurance is a plus.
• Proficiency with modeling software (SAS preferred)