28 applicants

Company

Legal & General America · 17 hours ago

Data Scientist

Frederick, MD

Full-time

Remote

Mid Level

$104K/yr - $143K/yr

3+ years exp

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Comp. & Benefits

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Responsibilities

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, creating machine learning models and pipelines.

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.

Other duties as assigned.

Qualification

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Statistical data analysisMachine learning modelingPythonMicrosoft ExcelDatabase platformsData extractionData analysisData visualizationSQLBI toolsMicrosoft WordTableauSpotfireBehavioral economicsDocumentation skills

Required

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.

1 – 3 years 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.

Proficient in statistical data analysis and machine learning modeling

Proficient in Microsoft Excel and Word and one or more database platforms

Understand how to analyze large, complex, multi-dimensional datasets and prescribe action

Proficient with statistical analysis tool such as Python

Experience with BI tools such as Tableau or Spotfire

Good working knowledge of SQL

Excellent understanding of machine learning techniques and algorithms

Basic understanding of behavioral economics

Excellent communication skills, both written and oral

Strong organization and documentation skills

“Self starting” with internal motivation and initiative

Demonstrates the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness