01Overview
Description :
About Tatvic :
Tatvic Digital Analytics is a Google Premier Partner specializing in Marketing Analytics, Cloud, and AI solutions.
With 16+ years of experience, Tatvic works with leading enterprises across BFSI, Auto, OTT, and Retail to unlock growth using data and intelligence. As part of our next phase, we are building cutting-edge capabilities in Agentic AI, combining machine learning, LLMs, and automation to transform decision-making systems.
Role Overview :
We are looking for a Data Scientist with strong applied AI capabilities to work on next-generation use cases involving LLMs, Agentic systems, and predictive modeling, especially in BFSI contexts.
This role requires a balance of classical machine learning expertise and modern LLM-based system design - including RAG pipelines, agent orchestration, and model evaluation. You will work closely with engineering, strategy, and delivery teams to design and deploy scalable AI solutions.
This is for one of the largest new-age digital banks in Singapore.
Key Responsibilities :
1. Data Science & Modeling :
- Build and deploy predictive models using regression, classification, and recommendation techniques (e.g., collaborative filtering).
- Apply statistical and ML techniques to solve business problems, especially in BFSI domains such as risk, fraud, segmentation, or personalization.
- Perform feature engineering, model selection, and performance optimization.
2. LLM & Agentic AI Development :
- Design and implement RAG (Retrieval-Augmented Generation) pipelines with vector database integration.
- Build and orchestrate AI agents using frameworks like LangChain, AWS Bedrock Agents, or similar.
- Develop end-to-end LLM-powered workflows and automation systems.
3. Prompt Engineering & Evaluation :
- Design, test, and optimize prompts for various use cases.
- Establish LLM evaluation frameworks (accuracy, hallucination detection, relevance, latency).
- Implement guardrails and safety mechanisms for responsible AI usage.
4. Model Deployment & Orchestration :
- Work with engineering teams to deploy models in production environments.
- Design scalable pipelines for model orchestration and monitoring.
- Ensure robustness, scalability, and performance of AI systems.
5. Collaboration & Innovation :
- Work closely with cross-functional teams (Delivery, Strategy, Engineering) to translate business needs into AI solutions.
- Contribute to internal AI accelerators and reusable frameworks.
- Stay updated with latest advancements in LLMs, Agentic AI, and applied ML.
Required Skills & Experience :
- 4 - 7 years of experience in Data Science / Applied AI / Machine Learning.
- Strong hands-on experience with regression, classification, and recommendation systems.
- Experience working in BFSI domain (banking, financial services, insurance) preferred.
- Practical experience with RAG pipelines and vector databases (e.g., FAISS, Pinecone, Weaviate).
- Experience with LLM frameworks such as LangChain, AWS Bedrock, or similar.
- Strong understanding of prompt engineering, LLM evaluation, and AI safety/guardrails.
- Experience building AI agents or automation workflows.
- Proficiency in Python and common ML/AI libraries. .
