Senior Data Scientist

We are looking for a driven and innovative Senior Data Scientist to join our Contact Centre AI Squad at Manulife Asia based in Singapore/Hong Kong.

As part of our AI and Generative AI initiatives, you will play a pivotal role in designing, developing, and deploying advanced AI solutions that strengthen contact centre operations and customer experience across Asia.

Your work will focus on building contact centre AI capabilities such as speech and interaction analytics, customer intent and sentiment understanding, intelligent quality assurance, agent assist, conversational AI, demand forecasting, workforce optimization, next best action, and responsible GenAI solutions that improve service quality, operational efficiency, and customer outcomes.

Position Responsibilities:

• Deliver machine learning, Generative AI, and advanced analytics capabilities across the contact centre value chain, from demand forecasting and customer intent understanding to agent assist, quality management, self-service, and customer experience.
• Lead the design, development, deployment, and continuous improvement of contact centre AI solutions across Asia markets, ensuring measurable business, operational, agent, and customer outcomes.
• Track, evaluate, and report AI project benefits, model performance, adoption, and operational impact; identify improvement opportunities and new contact centre AI use cases.
• Support the contact centre data strategy by improving data quality, optimizing internal interaction data assets, identifying relevant external customer service data sources, and strengthening data governance practices.
• Develop predictive, prescriptive, and GenAI-enabled solutions that support service demand forecasting, intelligent routing, agent productivity, quality assurance, self-service containment, proactive risk management, and better customer outcomes.
• Collaborate with global, regional, and in-market teams to establish contact centre AI modelling 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 contact centre 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 routing, personalization, next best action recommendations, conversation insights, and consistent service across voice and digital channels.
• Guide in-country AI and operations teams in designing, developing, and interpreting contact centre analytics and AI initiatives, with strong analytical rigor and clear measurement of outcomes.
• Support voice, chat, messaging, email, and self-service channels by applying analytics and AI to improve demand management, routing, service personalization, resolution efficiency, and agent effectiveness.
• Identify market, product, channel, and customer service 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 contact centre AI initiatives, optimize operational 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 service initiatives, contact centre analytics, and model-driven operational 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 contact centre AI business plans, roadmaps, priorities, and targets in collaboration with regional and local market stakeholders.

Required qualifications:

• 6+ years of experience in Data Science and Machine Learning, preferably within the retail financial services industry; prior experience in contact centre, customer service, or customer experience analytics is a significant advantage.
• Hands-on experience in multivariate analysis, modelling, segmentation, and contact centre analytics using statistical techniques, including speech, text, interaction, customer journey, and operational performance analytics.
• Expert in both concept and building AI/ML models, also in using data mining languages/tools e.g., 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.

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.