Gen AI Data Scientist

4 days ago

Singapore Income Insurance Limited Full time $120,000 - $180,000 per year
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:

  • At least 3–5 years of experience in a data science role, with relevant experience in AWS platform and/or Microsoft Copilot Studio.
  • 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 Flow 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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