Description
- Apply data science techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.
- Identify and test hypotheses, ensuring statistical significance, as part of building predictive models for business application.
- Translate quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
- Enable the business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes.
- Assist in customizing analytic solutions to specific client needs.
- Work on all components of projects considered low to moderate complexity and smaller components of complex projects.
- Engage with the Data Science community to develop and share techniques and best practices.
- Participate in cross functional working groups.
- Domestic travel required up to 10%.
- Telecommuting permitted up to 60%.
Qualifications
Employer will accept a Master’s degree (or foreign equivalent) in Statistics, Data Science, Statistical Science or related field. In the alternative, the employer will accept a Bachelor’s degree (or foreign equivalent) in Statistics, Data Science, Statistical Science or related field and one (1) year of experience in the job offered or in an Analyst I, Data Science-related occupation.
Position requires demonstrable experience in the following, which can be gained in a professional or academic setting:
- Demonstrating strong analytical skills with solid understanding of statistics and predictive modeling concepts and techniques as applied to insurance operations.
- Demonstrating an understanding of internal and external data sources, their dependencies, and appropriate uses for each for insurance operations.
- Demonstrating experience with statistical software packages (R, SAS, Python, and Emblem) to facilitate data gathering and preparation and building of predictive models.
- Building predictive models, including exploratory data analysis, appropriate data partitioning, selecting appropriate response variable, understanding of appropriateness and tradeoffs of possible model forms, feature engineering, feature selection, model tuning and fit, and model assessment.
- Working with insurance operations and the procedures of Financial, Underwriting, Claims, Statistical, Information Technology, Legal, and Sales departments.
- Demonstrating experience with exchanging ideas and conveying complex information clearly and concisely, including verbally, in writing, and via presentation to key stakeholders.
- Collaborating with partner teams to implement predictive models, including supporting material and responding to Department of Insurance.
- Domestic travel required up to 10%.
- Telecommuting permitted up to 60%.
