Data Scientist (VP/AVP)

Tangspac Consulting Group; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tangspac Consulting Group is seeking a senior AI/ML engineer to design, develop and deploy machine learning models for business applications across domains. You will build AI-driven solutions including recommendation systems, Next Best Action, predictive analytics, portfolio optimisation and risk modelling, and develop Generative AI apps using LLMs, RAG, prompts and Agentic AI frameworks.

The role requires hands-on ML, Python and SQL, PyTorch/TensorFlow, LangChain, cloud platforms,

Qualifications

• Hands-on data science and ML/AI experience (3–7+ years).
• Proficient in Python and SQL.
• Experience with ML/DL, NLP, and frameworks (PyTorch, TensorFlow, Scikit-learn).
• Hands-on experience with Generative AI, LLMs, RAG, Prompt Engineering, and Agentic AI.
• Familiarity with LangChain, LangGraph, vector databases, and embedding models.
• Experience with cloud platforms (AWS/Azure/GCP), Docker, Kubernetes, CI/CD, and MLOps/LLMOps.
• Experience deploying AI/ML models in production environments.

Responsibilities

• Design, develop, and deploy ML/DL models for business applications.
• Build AI-driven solutions including recommender systems, Next Best Action, analytics, portfolio optimisation and risk modelling.
• Develop Generative AI applications using LLMs, RAG, prompts and Agentic AI frameworks.
• Build scalable AI/ML pipelines and production-ready solutions using MLOps/LLMOps practices.
• Collaborate with business stakeholders, product owners and engineering teams to industrialize AI solutions.
• Contribute to AI Centre of Excellence, governance and responsible AI adoption.
• Implement model monitoring, explainability, performance optimisation and data quality practices.

Skills

Python

SQL

Machine learning

Deep learning

NLP

Explainability

Stakeholder communication

Education

Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or related field

Tools

PyTorch

TensorFlow

Scikit-learn

LangChain

LangGraph

Vector databases

Embedding models

AWS

Azure

GCP

Docker

Kubernetes

CI/CD

MLOps/LLMOps

Job description

Key Responsibilities

• Design, develop, and deploy machine learning and deep learning models for business applications.
• Build AI-driven solutions covering recommendation systems, Next Best Action, predictive analytics, portfolio optimisation, and risk modelling.
• Develop Generative AI applications using LLMs, RAG, Prompt Engineering, and Agentic AI frameworks.
• Build and maintain scalable AI/ML pipelines and production-ready solutions using MLOps/LLMOps practices.
• Collaborate with business stakeholders, product owners, and engineering teams to industrialize AI solutions.
• Contribute to AI Centre of Excellence development, AI governance, and responsible AI adoption.
• Implement model monitoring, explainability, performance optimization, and data quality practices.

Key Requirements

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 3-7+ years of hands-on experience in Data Science, AI, or Machine Learning.
• Strong programming skills in Python and SQL.
• Experience with machine learning, Deep Learning, NLP, and frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Hands-on experience with Generative AI, LLMs, RAG, Prompt Engineering, and Agentic AI.
• Familiarity with LangChain, LangGraph, vector databases, and embedding models.
• Experience with cloud platforms (AWS/Azure/GCP), Docker, Kubernetes, CI/CD, and MLOps/LLMOps.
• Experience developing and deploying AI/ML models in production environments.

Preferred Experience

• Banking, Financial Services, or Wealth Management domain experience.
• Exposure to investment analytics, portfolio optimisation, recommendation systems, or personalisation.
• Experience in AI governance or setting up an AI Centre of Excellence.
• Strong stakeholder management and communication skills.