This role is responsible for developing a wide variety of predictive models and analytical tools that will enable our client achieve their profitability and growth goals. The role will include applying sophisticated predictive modelling 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 team members and modelling groups. The role will provide highly technical analytical assessments of business issues to a mixture of technical and nontechnical audiences across the organisation to enable data-driven strategic decision-making.
Key Tasks & Responsibilities;
• Collaborate with business partners and other team members to develop appropriate statistical approaches and tools that will drive strategic decision making.
• Research, recommend, develop and implement new and/or alternative modelling methodologies and analytical solutions to complex problems central to our business.
• Perform complex, technical, and creative predictive analytics projects for use by a variety of business operations and/or functional groups (e.g. Distribution, Marketing, Claims etc.).
• Understand the competitive marketplace, business issues and data challenges in the country markets to deliver actionable insights, recommendations and business processes.
• Manage and contribute to 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.
• Identify and present findings, share actionable insights, and make recommendations that impact profitability, growth and/or customer satisfaction.
• Effectively communicate results in written, oral and presentation formats to management and stakeholders
• Provide mentorship, guidance, technical support, and training to data scientists across the team.
• Master's/PhD degree in Mathematics, Computing, Statistics or another quantitative field
• For non-Masters’ Degree candidates, Bachelor's Degree (minimum 2.1) and proven applied business / non-academic experience.
Knowledge & Experience:
• Experience with statistical techniques including generalized linear models, survival models, random forests, neural networks, clustering, and Bayesian approaches to data analysis.
• Identification of relevant statistical techniques for addressing various problems.
• Strong technical background; proficient with at least one language for predictive modelling and data analysis, such as R, Python or SAS.
• Experience with large analysis datasets, methodologies, and Enterprise-scale database systems.
• Advanced analytical/problem solving and research skills.
• Ability to identify and communicate limitations of tools and methods
• Proficient in predictive analytics including real-world experience in model development, validation, implementation, and testing.
• 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.
For more information please contact Paul at 016099404 or [email protected]
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