Lead Data Scientist - Insurance Analytics - J12995

Pinpoint Asia; Hong Kong; On-site; HKD 800,000 - 1,400,000; Full time

Job summary

Pinpoint Asia is seeking a Lead Data Scientist for Insurance Analytics in Hong Kong. You will bridge advanced machine learning with commercial insurance outcomes, focusing on value realization and strategic initiatives.

You will lead high-visibility analytics projects, build Python models from scratch, and partner with engineering to scale solutions on AWS, while defining KPIs and communicating with senior stakeholders.

Qualifications

• 8–12+ years of progressive experience in data science or analytics.
• Deep insurance/financial services domain knowledge.
• Strong coding skills in Python and SQL.
• Proven track record of deploying analytics on AWS.

Responsibilities

• Lead analytics and AI initiatives using Customer 360 data for segmentation, cross‑selling and next‑best‑action models.
• Own hypothesis-driven experimentation with A/B and multivariate tests.
• Remain hands-on, building Python-based machine learning models from scratch.
• Collaborate with engineering to productionize and scale algorithms on AWS.
• Define KPIs, quantify uplift, and present insights to senior stakeholders.

Skills

Python

SQL

Leadership

Tools

AWS

Job description

Lead Data Scientist - Insurance Analytics - J12995

About the Client: Our client is a globally recognized market leader in the Life, Health, and Wealth Management sectors. They are currently undergoing a massive, highly funded transformation to become a truly AI‑first organization. By building a state‑of‑the‑art enterprise data foundation, they are empowering their business units to leverage machine learning and GenAI at scale. This is an environment that champions innovation, heavily invests in modern cloud infrastructure, and places data science directly at the heart of its commercial growth strategy.

The Role & Landscape: Sitting directly within the business-facing Data & Analytics leadership team, you will bridge the gap between advanced machine learning and commercial insurance outcomes. You will not be bogged down by platform delivery or data governance; instead, you will focus purely on value realization.

Lead highly visible analytics and AI initiatives utilizing Customer 360 data to drive client segmentation, cross‑selling, and next‑best‑action models.

Own the hypothesis‑driven experimentation framework, designing robust A/B and multivariate tests to ensure business decisions are statistically sound.

Remain highly hands‑on, designing and building Python‑based machine learning models from scratch.

Partner closely with technology engineering teams to productionize and scale your algorithms on AWS.

Define KPIs, quantify causal uplift, and present actionable decision intelligence to senior non‑technical stakeholders.

What We Are Looking For:

Experience: 8–12+ years of progressive experience in data science, advanced analytics, or decision science.

Domain Expertise: Deep understanding of the insurance or broad financial services landscape (Life & Health, Wealth & Pension, distribution effectiveness, advisor enablement).

Technical Stack: Exceptional, hands‑on coding proficiency in Python and SQL.

Cloud: Proven track record of taking analytics solutions from prototype to production on AWS.

Methodology: Strong grasp of hypothesis testing, test‑and‑control mechanisms, and causal impact measurement.

Mindset: A consultative, growth‑oriented leader who thrives at the intersection of business, analytics, and technology. Prior consulting experience is highly advantageous.