At Manulife, data scientists collaborate with engineers, IT, and experts to build analytical models and data architectures for solving business problems within a modern MLOps framework! The Data Scientist is accountable for delivering business value with data by focusing on key corporate objectives, including portfolio optimization, expense efficiency, growth acceleration, digital customer leadership, fraud detection, and high-performance of the team. The Data Scientist is responsible for crafting, building, and deploying business interpretable and performant analytics solutions and applications. Collaborates with data and ML engineers to build scalable self-service tools for the analytics team. The Data Scientist leverages and shares their deep knowledge of, and experience with, a wide variety of data analytics practices and methods. The Data Scientist helps others to improve their knowledge and understanding of the use of data and technology. Position Responsibilities: Bridging between data assets, technology, and business expertise Collaborate shoulder-to-shoulder with business experts. Understand the business, the associated processes, systems & data environment. Research, explore, and experiment with data driven business ideas. Research & leverage published material to gain a comprehensive understanding of data science practices and methods. Crafting and building business interpretable and performant analytics solutions Develop and implement data analytics enabled solutions to improve and re-imagine business process, to generate insights, and support strategy development. Work on problems of diverse scope and complexity requiring the in-depth analysis of data. Quickly develop enough business insight to connect data sources across multiple diverse and complex systems. Generate relevant, actionable insights based on iterative data analysis, translating data-driven output into business language, and making appropriate recommendations to business partners. Work closely with business teams and data science engineers to collaboratively build and deliver rich data content for analysis. Deploy rich data and analytics content in business applications. Understand how the analysis of data impacts a broader business strategy, including the core drivers of business value. Prepare cases on the benefits of the analytics work. Elevate data and analytics skills in the business Help business partners better understand the use of data, drawing on a detailed understanding of data analytics and predictive modeling. Identify and guide natural data champions to improve the profitable use of data. Learn salient business concepts from data champions and enable them to creatively use data assets.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees