Data Scientists Banking

VAM Systems is currently looking for Data Scientists - Banking for our Bahrain operations with the following skillsets and terms & conditions:

Years of Experience: 7 10 years

Qualification

Bachelors Degree in Computer Science / Engineering
Preferably BE Computer Science & Engineering

Professional Training Required: Machine Learning Deep Learning MLOps AI in Financial Services.
Professional Qualification Required: Google Professional ML Engineer Microsoft AI Engineer Associate Professional Licenses Required Not applicable.
Professional Certifications Required: TensorFlow Developer Certificate AWS Certified Machine Learning.

Must-Have:

Proven hands-on delivery experience in banking financial institutions or insurance within Gen AI solutions such as chatbots document analysis etc. leveraging RAG and robust architecture with proper governance and security measures

Several years of ML experience with implemented use cases.
Hands-on work experience most of which in banking financial institutions or insurance industries.

Experience required:

Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms.
Experience with model evaluation and performance metrics.

Familiarity with AI use cases in banking (e.g. fraud detection personalization) Knowledge of data preprocessing and feature engineering.
Ability to work with cloud-based ML platforms (e.g. Azure ML AWS SageMaker). Understanding of MLOps and model lifecycle management.
Ability to communicate insights and build explainable AI models.


Core AI / NLP Engineering

Python (PyTorch TensorFlow LangChain Hugging Face OpenAI API Anthropic Claude etc.)

LLM fine-tuning (LoRA PEFT prompt tuning)

Retrieval-Augmented Generation (RAG) vector databases (Pinecone FAISS Weaviate Chroma)

Prompt engineering and orchestration (LangChain LlamaIndex Semantic Kernel DSPy)

Knowledge of embeddings tokenization and transformer architecture

Cloud AI tools: AWS Bedrock Azure OpenAI Vertex AI OpenSearch ElasticSearch

Model evaluation: hallucination detection grounding and benchmarking (BLEU ROUGE TruthfulQA etc.)

Software Engineering & Backend Integration

RESTful and GraphQL APIs webhooks

Containerization and deployment (Docker Kubernetes CI/CD)

Authentication and user/session management

Data pipelines and microservices

Knowledge of frameworks like FastAPI Flask NestJS or Express

Integration with enterprise data (SharePoint Salesforce SQL internal APIs)

Agent Orchestration & Tooling

LangGraph AutoGen CrewAI Flowise or similar agent frameworks

Task-decomposition and reasoning chains

Function calling tool use and API chaining

Memory design (short-term vs long-term)

Context management and grounding strategies.

Joining time frame: (15 - 30 days)

Remote Work :

No

Employment Type :

Full-time