Data Science Analyst
7 days ago
ARM Data Science – Non-Price Predictive Modeling is seeking a highly motivated Data Scientist who is eager to make an impact on the complex and evolving insurance industry. The Non-Price Predictive Modeling team is responsible for applying sophisticated predictive modeling and analytical analysis to a broad range of business problems; communicating the results of their work to stakeholders; and providing guidance and peer oversight to other modeling groups. You will leverage primary data, advanced quantitative modeling and financial analysis to develop predictive models and analytical tools that enable data-driven strategic decision-making. This role requires broad knowledge of predictive analytics techniques and advanced application of those techniques to a variety of business issues. You will provide highly technical analytical assessments of business issues to a mixture of technical and non-technical audiences.
Responsibilities:
• Collaborate with other business partners to develop appropriate statistical approaches and tools that will drive strategic decision making related to fraud, claims analytics, reserving, trends, and other challenging problems central to our business.
• Research, recommend, and implement new and/or alternative statistical and other mathematical methodologies appropriate for the given model or analysis.
• Perform highly complex, technical, and creative predictive analytics projects.
• Manage and prioritize multiple moderate-to-highly complex projects including gathering business requirements, developing project goals and requirements, coordinating project timelines, and communicating project status and deliverables with customers and management.
• Understand the competitive marketplace, business issues, and data challenges to deliver actionable insights, recommendations, and business processes.
• Present findings, share insights, and make recommendations that impact profitability, growth and/or customer satisfaction.
• Effectively communicate results in written, oral and presentation formats.
Qualifications:
• Bachelor’s degree or higher in Mathematics, Economics, Statistics or any other quantitative field or comparable actuarial education/designation preferred; plus, a minimum of 2 to 4 years of relevant work experience.
• Advanced analytical/problem solving and research skills.
• Proficient in predictive analytics including real-world experience in model development, validation, and testing.
• Proficient with at least one language for data analysis, such as R, Python or SAS.
• Experience with large analysis datasets and Enterprise-scale database systems.
• Experience with statistical techniques including generalized linear models, survival models, random forests, clustering, NLP/OCR and Bayesian approaches to data analysis.
• Strong verbal and written communication skills, interpersonal skills, and ability to clearly and effectively communicate technical results to a non-technical business audience.
• Knowledge of insurance principles, underwriting and ratemaking concepts and the various functions of an insurance organization, including Finance, Underwriting, Sales and Claims desirable.
• Ability to perform high-level work both independently and collaboratively as a project team member or leader.
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