Data Scientist (Hybrid Worcester, MA or Remote)

The Hanover Insurance Group•Worcester, MA

1d•$85,000 - $105,000•Hybrid

About The Position

The Data Scientist designs, implements, and evaluates advanced statistical models, machine learning algorithms, and tools for application in the business’s most complex issues. The Data Scientist builds econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling, simulations, and so forth. In this capacity, the Data Scientist researches new ways for predicting and modeling end-user behavior as well as investigating data summarization and visualization techniques for conveying key applied analytics findings. The Data Scientist also performs ad-hoc data mining and exploratory statistics tasks on very large data sets related to the business’s strategies. In this capacity, the Data Scientist will also prepare reports and presentations for relevant stakeholders that will give insights for departmental as well as business-wide decision making. Establishment of data governance and regulatory practices will be adhered to.

Requirements

Typically has 2+ years of related experience and a bachelor’s degree, Master’s, or Ph.D.’s degree is preferred. Relevant Masters or Ph.D. can count towards work experience.
Has a good understanding of relevant insurance analytics and metrics and is able to incorporate this understanding in work product.
None or very limited insurance business knowledge is expected at the entry level. It's recommended to have a training plan and prioritize the insurance knowledge needed over time.
Able to communicate through storytelling and collaborate with business partners.
Demonstrates CARE values in daily work.
Know basic concepts on Math, Stats and Modeling.
Build simple models through school projects or prior work experience.
Able to explain past technical projects clearly.

Responsibilities

Participate in advanced analytic work and predictive modeling projects using statistical and machine learning/deep learning techniques to solve business problems.
Collaborate with product management and the LOBs to understand company needs and devise possible solutions.
Keep up to date with the latest technology trends.
Communicate results and ideas to key decision-makers.
Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
Collect data from all kinds of different sources, from web APIs to internal databases encoded in SQL.
Optimize joint development efforts through appropriate database use and solution design.
Document the development and the design of the solutions built.
Begin to work on relatively simple projects with minimal supervision.
Create meaningful data visualizations that communicate your findings and relate them to how your insights create business impact.