Data Scientist - 1
Frederick, MD 21701
Support the management of all insurance product lines by creating advanced statistical, predictive, and machine learning models focused on: (1) developing and maintaining the capability to understand and proactively influence the drivers of customer behavior, (2) optimize the use of data in the risk pricing and underwriting process, (3) design experiments, test hypotheses, build models, and conduct advanced data analysis.
Analyze and solve analytics problems and communicate the results, advantages and limitations, of the methodologies used in the analysis. Define the validity of information, how long the information is meaningful, and what other information it relates to.
Identify necessary data required to support initial and ongoing modeling including selecting features, building, and optimizing data using predictive modeling. Collaborate with subject matter experts to select relevant sources of information. Procure data directly from relevant platforms, internal and external providers, or by working with IT resources.
Model and frame meaningful business scenarios that will impact critical business processes and/or decisions.
Develop a set of actionable parameters and support creation of business models based on those parameters that are designed to influence customer behavior with respect to profitable levels of persistency and mortality.
Research current and emerging underwriting data and risk assessment algorithms based on that data, develop a set of actionable parameters for nontraditional underwriting factors, and support the creation of business models that supplement or replace traditional underwriting requirements.
Work in conjunction with business analysts to suggest other products of interest to our customers.
Develop experimental design approaches to validate findings or test hypotheses and validate analysis by comparing appropriate samples.
Recommend ongoing improvements to current data analysis methods and algorithms that will lead to actionable findings, including new information.
Provide business metrics for overall projects to show improvements.
Evaluate special underwriting practices and facilitate partnerships with underwriting and reinsurers to identify new opportunities and quantify their projected impact on mortality expectations.
Develop a continuous internal and external mechanism to collect and analyze underwriting technology and techniques to place and maintain LGA on the forefront of emerging practices.
Develop a set of actionable parameters of post issue health changes and lifestyle patterns and support the creation of a business model based on those parameters.
Assist in the periodic review and development of actuarial assumptions used for financial analysis of inforce business.
Provide support to marketing and administrative areas as required.
Required Knowledge, Skills, and Abilities: (Submission Summary)
1. Master’s degree in /Statistics/Mathematics/Computer Science/ Data Science /Actuarial Science or quantitative field equivalent or (Bachelor’s degree with 3+ years relevant Data Science and/or Predictive Analytics experience.)
2. 1+ years (3+ years with Bachelor's degree) of school-project and/or internship experience in applied statistics and data science working with analytical life cycle, including data extraction, analysis to visualization then operational use. Prior data science work experience a plus.
3. Familiarity with life insurance, especially mortality and lapse modeling, and underwriting, preferred.
4. Completion of any actuarial exams, and actuarial credentials (ASA/FSA) is a strong plus.
5. Proficient in statistical data analysis and modeling
6. Proficient in Microsoft Excel and Word and one or more database platforms
7. Understand how to analyze large, complex, multi-dimensional datasets and prescribe action
8. Proficient with statistical analysis tool such as R, SAS, or Python
9. Experience with BI tools such as Tableau or Spotfire
10. Good working knowledge of SQL
11. Excellent understanding of machine learning techniques and algorithms
12. Basic understanding of behavioral economics
13. Excellent communication skills, both written and oral
14. Strong organization and documentation skills
15. “Self starting” with internal motivation and initiative
16. Demonstrates the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness.
17. If you do not live within a commutable distance to our office in Urbana, Maryland, are you willing to relocate.
18. If extended an offer, would you be able to start employment with Legal & General America within 2-3 weeks of acceptance?
19. What are you looking for in the next company you work?
20. If you are currently employed, what promoted you to look for a new opportunity.
21. Have you applied to or been in contact with Legal & General America in the last 12 months?
22. Have you applied to a job or been contacted by Legal & General America in the last 12 months?
23. Please provide brief descriptions of your project using applied statistics and data science. Also include the analysis environments, platforms and tools used for the projects.
24. Are you familiar with life insurance mortality modeling and underwriting?
25. Salary Expectation?
26. US Citizen or Green Card holder.
27. Complete Current Address?