The Data Scientist role provides the opportunity to support analytics‑enabled initiatives by developing and delivering data analysis and models that address defined business needs. As part of the MBPS Advanced Analytics team, the role contributes to Manulife's mission of helping customers make decisions easier and lives better by producing reliable, actionable insights from data. The successful candidate will work closely with internal teams and business stakeholders to execute analytics tasks across various use cases within the customer lifecycle. Through this role, they will gain hands‑on experience working with real business data, established analytics processes, and end‑to‑end solution delivery.
Position Responsibilities
- Develop and implement analytics‑enabled solutions to improve business processes, generate insights, and support business strategy.
- Own and deliver end‑to‑end analytics projects of moderate complexity, while contributing to larger, more complex initiatives.
- Analyze large and complex datasets to generate actionable insights and translate findings into clear business recommendations.
- Collaborate closely with business stakeholders and subject matter experts to understand data sources, processes, and business needs.
- Provide guidance and mentorship to junior data scientists and contribute to knowledge sharing within the analytics community.
Required Qualifications
- Minimum of 5 years of applicable experience with advanced knowledge of programming languages and concepts (Python and SQL, SQL queries)
- Knowledge in data visualization tools such as PowerBI, plotly, R Shiny, etc. (or other equivalent data visualization tools)
- Strong knowledge of machine learning and AI algorithms
- Advanced degree in Statistics, Mathematics, Computer Science, Engineering, or a related field; or a Bachelor's degree with equivalent technical experience
Preferred Qualifications
- Experience applying statistical modeling and machine learning techniques (e.g., regression, clustering, decision trees, survival analysis)
- Working knowledge of AI, GenAI, or advanced analytics toolkits and frameworks, including exposure to Retrieval‑Augmented Generation (RAG)
- Exposure to cloud platforms (e.g., Azure, AWS, or GCP) for data processing, model development, or solution deployment
- Experience with data visualization tools such as Tableau, Qlik, or open‑source libraries (e.g., ggplot, d3)
- Familiarity with relational database models and large‑scale data environments
- Proficient in querying and analyzing both structured and unstructured data (SQL, NoSQL, JSON, MongoDB)
- Experience designing or implementing scalable, end‑to‑end analytics processes with appropriate governance and tracking mechanisms
When You Join Our Team
- We'll empower you to learn and grow the career you want.
- We'll recognize and support you in a flexible environment where well‑being and inclusion are more than just words.
- As part of our global team, we'll support you in shaping the future you want to see.
