Data Scientist II

Employer:

Arbella Insurance Group

Job Site:

1100 Crown Colony Drive, Quincy, MA 02169

Job Title:

Data Scientist II

Job Duties:

Responsible for designing, constructing and implementing predictive and prescriptive models across personal and commercial lines of insurance using statistical techniques, machine learning and data analysis.

Design, construct and implement predictive models using GLM, RF, GBM, SVM and other statistical techniques;

Develop unsupervised machine learning models for anomaly detection, clustering, topic modeling and variable reduction;

Leverage big data technology to extract insights from unstructured and semi-structured data including text analytics and data visualization;

Collaborate with modeling analysts and data scientists to aggregate, transform and analyze data for predictive modeling projects;

Work closely with subject matter experts to solve business problems and effectively communicate findings;

Contribute to modeling best practices including model selection, validation and monitoring;

Develop pricing plans and contribute to product design and research strategies;

Conduct research to explore statistical techniques and application to the business; and prepare written and oral reports to communicate findings and recommendations to stakeholders;

Keep abreast of emerging advanced modeling techniques, industry trends, and advancements in data science, predictive analytics and actuarial science;

Collaborate with cross-functional teams during high-level company project teams.

Minimum Requirements:

Master’s degree or foreign equivalent in Statistics, Applied Statistics, Mathematics, Actuarial Science or related field and 2 years of statistics modeling experience within the Property & Casualty Insurance Industry.

Experience must include:

2 years pricing analysis experience within the Property & Casualty Insurance Industry;

2 years of risk analysis and risk management experience within the Property & Casualty Insurance Industry;

2 years of experience using advanced statistical techniques including GLM, RF, GBM and SVM;

2 years of experience using programming languages such as SAS, R, Python and SQL;

2 years of experience in API integration;

2 years of experience using database principles and working with large datasets;

2 years of experience using insurance data to understand data distributions and appropriate transformations.

Experience may be gained concurrently.

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