Sun Life Hiring! Full Time Associate Director - Senior Manager, Data Scientist in Kowloon, Hong Kong - Ricebowl

Vous êtes unique, comme le sont votre parcours, votre expérience et votre façon de voir les choses. Ici, on vous encourage et on vous motive à donner le meilleur de vous-même, et on vous donne les moyens de le faire. Vous travaillerez avec des collègues dynamiques – experts dans leur domaine – qui sont impatients de partager leurs connaissances avec vous. Vous aurez des gestionnaires inspirants qui vous aideront à développer votre potentiel et à atteindre de nouveaux sommets. Chaque jour, vous aurez de nouvelles occasions de rendre la vie de nos Clients plus radieuse – ils sont au cœur de tout ce que nous faisons. Découvrez comment vous pouvez faire une différence dans la vie des gens, des familles, des collectivités – ici et partout dans le monde.

De scription de poste :

The Associate Director, Data Scientist is a senior, business‑facing data science role, sitting within Data & Analytics, responsible for driving insurance business outcomes through AI, Advanced analytics and machine learning, leveraging our data foundation.

This business-side data science leadership role focuses on transforming client, policy, interaction, and behavioral data into actionable insights, next-best actions, and decision intelligence for the Life & Health and Wealth & Pension businesses.

The role combines hands‑on AI / data science capability (Python, AWS), strong insurance business acumen, and AI leadership, including responsible use of machine learning and GenAI to problem solving and stakeholder engagement. It is accountable for analytics and AI value realization from C360, not for platform delivery or data governance.

Key Responsibilities

Insurance Analytics & AI Use Case Leadership

• Lead insurance‑specific analytics and AI use cases built on Client 360, including:

• Client segmentation and profiling
• Cross‑sell, up‑sell, and next‑best‑action models for advisors
• Client lifecycle, retention, and persistency analytics
• Personalisation client engagement and targeting

• Frame analytics and AI initiatives around clear insurance business outcomes (growth, advisor productivity, client retention)
• Define KPIs and track measurable commercial and operational impact

Hypothesis‑Driven Data Science & Experimentation (AWS / Python)

• Own a hypothesis‑driven analytics approach, translating business questions into testable hypotheses
• Design and execute experiments and test‑and‑control mechanisms, including:
  • Champion / challenger models
  • A/B and multivariate testing
  • Controlled rollouts for analytics‑driven decisions
• Ensure experiments are statistically sound, interpretable, and aligned with insurance business constraints
• Quantify incremental impact and causal uplift, distinguishing signal from noise
• Embed closed‑loop learning to continuously refine models, rules, and decision logic

Hands‑on AI / Data Science Delivery

• Design, build, and deploy Python‑based data science and AI models
• Perform feature engineering using client, policy, interaction, and behavioural data
• Partner with technology and engineering teams to productionize analytics and experiments on AWS
• Ensure models and experiments are robust, scalable, explainable, and suitable for regulated insurance environments
Monitor model and experiment performance over time and drive continuous improvement

Qualifications

Core Skills (Required)

• Strong hands‑on experience in Python for data science and machine learning
• Proven experience delivering analytics solutions on AWS
• Strong SQL and experience working with large client‑ or policy‑level datasets
• Track record of moving analytics from prototype to production

Experience & Domain

• 8–12+ years in data science, advanced analytics, or decision science
• Experience in insurance or financial services is strongly preferred
• Good understanding of insurance business levels is strongly preferred
  • Personalisation and targeted engagement
  • Client lifecycle and persistence
  • Distribution effectiveness and advisor enablement
• Familiarity with Client 360, CRM, or enterprise data platforms is a strong advantage

Leadership & Mindset

• A growth mindset to problem solve and curiosity to explore problems to be solved.
• Comfortable operating at the intersection of business, analytics, and technology
• Prior experience in business consulting and analytics advisory is a plus.

Catégorie d'emploi :

Advanced Analytics

Fin de l'affichage :

26/07/2026