Senior Data Scientist (Generative AI) - Professional

 Senior Data Scientist (Generative AI) 
 About The Role : 

We are seeking a highly skilled  Senior Data Scientist  to design and implement innovative AI systems for our team. The role involves building  Retrieval-Augmented Generation (RAG)  pipelines, fine-tuning large language models (LLMs), and developing advanced recommender systems and next-best-action frameworks. The ideal candidate has expertise in  data science ,  machine learning , and  AWS technologies , and thrives in solving complex challenges with a blend of creativity and technical acumen.
 Roles and Responsibilities   1. Generative AI and RAG Integration 

Design and implement  RAG workflows  that enhance LLMs (e.g.,  Anthropic Claude , OpenAI GPT) with real-time data from external knowledge sources.

Fine-tune pre-trained LLMs using domain-specific datasets to optimize response accuracy and contextual relevance.

Develop data augmentation pipelines for conversational AI systems that deliver context-aware, high-quality outputs.

 2. Advanced Recommendation Systems and Next-Best-Action Models 

Build and improve recommender systems using  collaborative filtering ,  content-based filtering , and  hybrid approaches .

Design and implement  rules-based next-best-action  models that use contextual and behavioral data to recommend optimal outcomes.

Leverage RAG methodologies to improve the real-time personalization of recommendations.

 3. Data Science and Analytics 

Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights from structured and unstructured datasets.

Build machine learning models to predict user behavior, optimize processes, and drive actionable insights.

Work with large-scale datasets using  AWS services , such as SageMaker, DynamoDB, and Aurora, to train and deploy AI models.

 4. RAG and Vector Search Development 

Implement  vector embeddings  for data retrieval and search using tools like  DynamoDB with Aurora  or other vector databases.

 Essential Requirements 

Bachelor’s,Master’s or Ph.D. in Data Science, Computer Science, Machine Learning, Statistics, or a related field.

 5+ years  of experience in data science, with a focus on  generative AI ,  RAG , or advanced recommendation systems.

Hands-on experience with LLMs (e.g.,  Anthropic Claude , OpenAI GPT) and embedding-based retrieval techniques.

Proficient in leveraging  AWS technologies  for model development and deployment.

Proficiency in Python or R and expertise in machine learning libraries like  TensorFlow ,  PyTorch , and  Scikit-learn .

Strong understanding of  retrieval-augmented generation (RAG)  pipelines and embedding-based systems.

Experience with  AWS services , including SageMaker, DynamoDB, and Aurora, for scalable AI solutions.

 Plus to Have 

Familiarity with MLOps pipelines, CI/CD practices, and production-grade deployments.

Knowledge of advanced analytical techniques, such as deep learning or natural language processing.