Gen AI Data Scientist - Singapore - Income Insurance Limited

    Income Insurance Limited
    Income Insurance Limited Singapore

    15 hours ago

    Insurance
    Description
    Job Description

    GEN AI Data Scientist – Data Analytics

    Responsibilities:
    • Take ownership of AI/ML use cases, from design and implementation to continuous enhancement.
    • Act as a technical specialist in AI, primarily focusing on Generative AI. Design and develop solutions to address various business challenges, particularly those related to optimizing operational efficiency.
    • Collaborate with other data engineers, analysts, data scientists, product specialists, and stakeholders to build well-crafted, pragmatic, and robust solutions that meet business requirements.
    • Stakeholder management and engagement: proactively engage with stakeholders to understand their needs and translate them into technical requirements for AI/ML modeling.
    • Maintain documentation of dataset curation, modeling approach, model performance, code changes, and workflows.
    • Demonstrate a strong understanding of data privacy regulations such as PDPA, and AI governance guidelines to ensure compliance.
    • Foster an innovative and growth-oriented mindset, continuously seeking opportunities to enhance AI/ML models and drive improvements across the organization.

    Requirements:
    • 3–5 years of experience in a data science role, with demonstrable expertise in the AWS platform. Experience with Microsoft Copilot Studio is a plus.
    • Bachelor's degree in computer science or equivalent.
    • Familiarity with techniques for Document Chunking, Embedding, and Information Retrieval for improving model accuracy and relevance.
    • Expertise in Prompt Engineering for designing and managing effective prompts.
    • Hands-on experience with AWS Bedrock, including deploying solutions using foundation models and integrating them into scalable applications using APIs and orchestration tools.
    • Experience in Agentic Workflow for maximizing the utility of models, including understanding user intent and context to drive meaningful interactions.
    • In-depth knowledge of supervised and unsupervised ML models – linear & logistic regression, clustering, tree-based models like random forest, bagging, and boosting models.
    • Proficient in SQL, Python, and Spark.
    • Proven experience in implementing MLOps practices on AWS.
    • Familiar with Data Warehouses such as Redshift, Hive, and S3.
    • Passionate about technology and always looking to upskill based on new developments in the AI space.
    • AWS or Microsoft certifications will be a plus.
    • Experience in the financial industry, telecommunications, or consulting is preferred
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