> Markdown version of [/jobs/ext/3565638-senior-data-scientist](https://www.wearedevelopers.com/jobs/ext/3565638-senior-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** Manulife - **Location:** Toronto, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Microsoft Azure, Big Data, Data Mining, R (Programming Language), Apache Hadoop, Apache Hive, Python (Programming Language), Machine Learning, SAS (Software), SQL Databases, Model-Driven Development, System Availability, Apache Spark, Generative AI, Data Strategy - **Published:** October 3, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/peciya26np ## About the Role * 6+ years of experience in Data Science and Machine Learning, preferably within the retail financial services industry, prior experience in health/insurance/reinsurance domain is a huge plus * Hands-on experience of multivariate analysis, modeling, segmentation and Health/claims analytics using statistical techniques * Expert in both concept and building AI/ML models, also in using data mining languages /tools eg, some or all of Python, SAS, R, SQL or equivalents * Experience in any big data/ cloud solution of Azure, Hadoop, Hive, Spark etc. is a plus * Strong experience in deploying analytics solutions including targeting, test and control development, response tracking and analysis * Experience translating complex business problems into analytical requirements and propose actionable solutions based on internal and external best practice. * Strong communication and presentation skills. Ability to persuade a wide range of colleagues * Ability to lead and build an initiative from scratch and to handle high level of ambiguity * Able to maintain strong, productive relationships with stakeholders and external partners * Able to work independently as well as a good team player * Highly regulated business environment by nature * Some analytical solution is difficult to measure the exact financial impact, or right on the path but no immediate big financial impact and how to align stakeholders * Data availability and data quality issues in certain markets can always be challenges to build sound analytical solutions * Deploy analytical findings require multiple efforts from multiple stakeholders from both regional and local * Manage stakeholders with conflicting objectives/priorities ## Description * Leverage data and advanced analytics techniques based on in-depth understanding of health business. * Build machine learning and GenAI solutions across health value chain. * Transform analytical insights and solutions into business actions with measurable benefits and integrating them into workflow process. * Utilize data science expertise to design and implement Health AI solution evaluation and monitoring frameworks. What motivates you? * You obsess about customers, listen, engage and act for their benefit. * You think big, with curiosity to discover ways to use your agile approach and enable business outcomes. * You thrive in teams and enjoy getting things done together. * You take ownership and build solutions, focusing on what matters. * You do what is right, work with integrity and speak up. * You share your humanity, helping us build a diverse and inclusive work environment for everyone., * Deliver machine learning, Generative AI, and advanced analytics capabilities across the health value chain, from prevention and engagement to claims, provider insights, and customer experience. * Lead the design, development, deployment, and continuous improvement of Health AI solutions across Asia markets, ensuring measurable business and customer outcomes. * Track, evaluate, and report AI project benefits, model performance, adoption, and operational impact; identify improvement opportunities and new Health AI use cases. * Support the health data strategy by improving data quality, optimizing internal data assets, identifying relevant external health and clinical data sources, and strengthening data governance practices. * Develop predictive, prescriptive, and GenAI enabled solutions that support profitable growth, proactive risk management, personalized health engagement, claims efficiency, and better customer outcomes. * Collaborate with global, regional, and in market teams to establish Health AI modeling standards, reusable solution patterns, governance frameworks, and responsible AI practices aligned with AI CoE standards. * Establish and maintain a regional model and AI solution repository to capture, monitor, diagnose, and continuously improve models and AI assets in production. * Provide expert guidance to in country analytics and AI teams on advanced quantitative analysis, model development, GenAI solution design, evaluation methods, and domain specific interpretation. * Translate complex health business needs into clear analytical requirements and scalable AI solutions, balancing speed to market, technical rigor, regulatory expectations, and operational feasibility. * Enable more effective engagement with prospects, customers, advisors, and distribution partners through data driven targeting, personalization, next best action recommendations, and health insight solutions across channels. * Guide in country AI teams in designing, developing, and interpreting campaigns and Health AI initiatives, with strong analytical rigor and clear measurement of outcomes. * Support bancassurance, digital, agency, and direct channels by applying analytics and AI to improve targeting, offer personalization, health engagement, and sales efficiency. * Identify market, product, channel, and health journey specific challenges, and propose practical AI and analytics solutions that are customer centric, scalable, and compliant. * Partner with regional and BU stakeholders to prioritize Health AI initiatives, optimize decisions and activities, and align use cases with strategic business value and customer needs. * Build regional and BU level result tracking, reporting, and best practice capabilities for AI-enabled campaigns, health analytics initiatives, and model driven business programs. * Identify root causes of underperformance and recommend actionable improvements across data, model design, deployment, adoption, and business execution. * Escalate emerging risks early and define mitigation actions for markets, including model risk, data limitations, adoption barriers, and regulatory or operational constraints. * Develop annual Health AI business plans, roadmaps, priorities, and targets in collaboration with regional and local market stakeholders.