Lead Ai Engineer

4 days ago

Singapore PRUDENTIAL ASSURANCE COMPANY SINGAPORE (PTE) LIMITED Full time

Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

Develop engineering standards and frameworks to automate and standardize the development of machine learning and generative AI, ensuring scalability, reliability, and adherence to FEAT principles and Singapore’s Veritas Guidelines.
Leverage feedback from stakeholders on Analytics Products to influence the product roadmap.
Conduct comprehensive analyses on customer trends, campaign effectiveness, and distribution channels using statistical and AI models, facilitating strategic business recommendations.
- To drive advance analytics excellenceDrive the professional development of the team, overseeing the code review and pull request processes for analytics projects.
Define and update coding and engineering standards, prioritizing the deployment of dependable analytics solutions.
Collaborate closely with business partners to identify their challenges and objectives, developing bespoke predictive models, statistical analyses, data reports, and performance metrics utilizing both traditional ML and generative AI techniques.

**Who we are looking for**:

- Demonstrable expertise in machine learning processes, including notable experience with generative AI.
- Proficiency in GIT, Python, SQL, DataBricks, MLFlow, and ML frameworks (e.g., scikit-learn, TFX, PyTorch).
- Extensive experience in:

- Cloud platforms (Azure, with GCP and AWS being advantageous)
- Adopting a DevOps mindset
- Transforming data science prototypes into production-ready solutions
- Enhancing existing ML frameworks and libraries
- Translating analytics findings into business decisions
- Collaborating with data scientists and non-technical stakeholders to drive actions based on data insights.

**Qualifications**:

- Master’s degree, PhD, or equivalent experience in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or a related field.
- Prior knowledge or experience in life insurance practices is highly desirable.

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