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Consultant, Enterprise Analytics (Data Science) - Job Opportunity at AIA

Singapore, Singapore
Full-time
Mid-level
Posted: May 19, 2025
On-site
SGD 120,000 - 180,000 annually based on Singapore market rates for mid-level data science roles in financial services

Benefits

Career development opportunities with focus on digital transformation
Training and upskilling in emerging technologies
Work on large-scale AI/ML implementations
Exposure to enterprise-level projects

Key Responsibilities

Lead development and implementation of ML and GenAI solutions for business optimization
Design and deploy production ML models using MLOps best practices
Manage ML workflows on Azure platform ecosystem
Implement AI governance and risk management frameworks
Monitor and maintain model lifecycle management
Collaborate with cross-functional teams on data infrastructure
Communicate technical findings to diverse stakeholders

Requirements

Education

Bachelor's degree in data science, statistics, computer science, mathematics, or related field

Experience

3 to 7 years of relevant hands-on experience in data science/machine learning

Required Skills

Python SQL Machine learning algorithms Scikit-learn PyTorch LangChain MLOps Azure ML Azure OpenAI Azure DevOps LLM RAG applications Project management Databricks (preferred)
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Sauge AI Market Intelligence

Industry Trends

Insurance sector is rapidly adopting AI/ML for risk assessment and customer experience enhancement Growing emphasis on responsible AI and governance frameworks in financial services Increased demand for MLOps expertise due to scale of AI implementations Rising importance of generative AI applications in enterprise contexts

Role Significance

Typically part of a 5-8 person data science team within larger enterprise analytics department of 20-30 people
Mid to senior individual contributor role with significant technical autonomy and strategic input on AI initiatives

Key Projects

End-to-end MLOps implementation for production AI systems Customer behavior prediction models Risk assessment automation Claims processing optimization using AI Document intelligence systems using GenAI

Success Factors

Strong foundation in both traditional ML and emerging GenAI technologies Ability to balance technical excellence with business value delivery Experience with enterprise-scale ML deployments Understanding of financial services regulatory environment Strong communication skills for stakeholder management

Market Demand

High demand with significant growth trajectory expected over next 3-5 years due to insurance industry's digital transformation initiatives and increasing focus on AI-driven solutions

Important Skills

Critical Skills

MLOps expertise due to focus on production deployment and scaling Azure cloud platform proficiency given technical stack GenAI knowledge for emerging use cases Communication skills for stakeholder management

Beneficial Skills

Insurance domain knowledge Databricks experience Cloud architecture understanding Agile project management

Unique Aspects

Opportunity to work on large-scale AI implementations in regulated environment
Focus on health and wellness solutions provides meaningful impact
Strong emphasis on AI governance and responsible AI practices
Combination of traditional ML and cutting-edge GenAI applications

Career Growth

2-3 years in role before progression, with accelerated growth possible based on project impact

Potential Next Roles

Lead Data Scientist ML Engineering Manager Head of AI/ML Technical Product Manager - AI Solutions

Company Overview

AIA

Leading pan-Asian insurance provider with strong focus on digital transformation and innovation

One of the largest insurance groups in Asia Pacific with significant technology investment capacity
Strong regional headquarters presence in Singapore with opportunities for cross-border projects
Traditional financial services environment transitioning to more agile, tech-focused culture with emphasis on innovation
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