Fall 2024 Data Science/Predictive Modeler Intern

Key Skills

Data cleaning / Data cleansing, Data science techniques, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Python Programming, R Programming, SAS, SQL

Job Description

The intern will conduct full cycle of the development of advanced analytical models under supervision to enable future growth and profitability for our book of business. The efforts include research, development, implementation, and maintenance of analytical solutions supporting various business areas e.g. pricing, underwriting, marketing, operation, and claims. The intern will conduct end to end formal modeling process including data gathering, data profiling, model construction, validation, and other related tasks; build predictive models that improve profitability through the creation of new rating plans with improved estimation and segmentation of insurance risk; collaborate with business unit leaders to deliver operational enhancements and cost efficiencies in the claims, underwriting, and customer service processes. The role is a unique opportunity to explore/apply advanced techniques while making tangible impacts to the business.

Essential Functions and Responsibilities

• Performs data mining and data cleansing tasks.
• Prepare datasets for modeling through balancing and validation.
• Produces predictive models which enable the creation of rating plans and evaluation of risk.
• Assists decision makers with studies that evaluate new business models to evaluate customers’ profitability including customers and/or risk segmentation, retention and lifetime value modeling.
• Hands-on modeling experience and deep understanding of both conventional quantitative analytics such as GLM, GLMM, Bayesian statistics, Actuarial methods and tree-based machine learning techniques like GBM, Random Forest, NLP, Topics Model and Deep Learnings
• Communicates to diverse audiences, including technical and non-technical.
• Manages projects of moderate complexity.
• Supports modeling requests made by other departments.
• Works closely with others to gain strong understanding of insurance concepts and processes.
• Perform other job-related duties as assigned.

Qualifications and Education

• Broad thinker with the ability to synthesize information from various sources and apply that information to concrete business problems. Strong decision-making skills.
• Solid skills and training in predictive modeling, data mining and other quantitative and research analytics (Multivariate Analysis, Bayesian Methods, Generalized Linear Models, Non-Linear Models, Decision Trees, Non- Parametric estimation, Machine learning techniques etc.).
• Strong programming ability in Python, SAS, SQL, R or other programming languages and proficiency in scripting languages and ability to build code and algorithms to tackle statistical problems.
• Excellent written and oral communication and presentation skills.
• Self-starter, critical thinking and strong individual contributor.
• Solid understanding of database principles and experience working with large databases.
• Knowledge of auto insurance will be a plus.
• Experience developing and implementing multivariate predictive models using GLM and other statistical methods preferred
• Masters in economics, statistics, or related field required, PhD preferred.

About the Company

The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner’s insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”.