Berkley Regional Marketplace (BRM) is a W.R. Berkley Company committed to providing small business customers with the next generation of small business solutions, including offering operational, underwriting and marketing opportunities. Good isn’t good enough for our Berkley Regional Marketplace team. We champion our customers, always seeking a smarter way to provide a more efficient and better user experience.
We are a proud member of W. R. Berkley Corporation, one of the largest commercial lines property casualty insurance holding companies in the United States. With the resources of a large Fortune 500® corporation and the flexibility of a small company, we exclusively work with select independent agents to bring technology solutions that help them build their business.
As a Sr. Data Scientist for Berkley Small Business, you will play an integral part in changing the way insurance is delivered. The role will allow you to apply cutting-edge machine learning algorithms to a variety of business problems, and your contributions could be add value immediately as you join a team committed to data-driven decision-making. This creates an environment where your models could be quickly implemented and have a real impact on the business. The role will provide exposure to a wide range of commercial insurance lines.
- Build internal platforms and infrastructure to speed up the data science life cycle.
- Define and change the way insurance is delivered to different areas of the company.
- Apply cutting-edge machine learning algorithms to a variety of business problems using data-driven decision-making.
- Build statistical models for the select and price insurance businesses.
- Evaluate and refine existing models to increase profitability.
- Extract and clean data for modeling purposes using SQL.
- Apply machine learning techniques and statistical methods such as GLMs. Leverage knowledge of statistics and machine learning techniques such as random forest, gradient boosting and k-means clustering to build accurate predictive models.
- Apply coding skills using GitHub, Bitbucket and Kaggle.
- Use programming skills in Python and R to build data pipelines, model data, create reports, and create model implementations.
- Collaborate with business experts to improve existing processes through analytics.
- Provide model results to senior leaders.
- Master’s degree in computer science, mathematics, statistics or data science.
- 3 years of experience in data science.
Must have some work experience with each of the following: programming in SQL to create clean and accurate datasets for analysis; programming in Python and R to build data pipelines, model data, create reports, and create model implementations within the insurance domain; knowledge of statistics and machine learning techniques such as random forest, gradient boosting and k-means clustering to build accurate predictive models; advanced experience working with generalized linear models to price insurance business.