Vitric Business Solutions - Data Scientist - NLP/Python

<p>Job Description :</p><p><br/></p><p>Key Responsibilities :<br/><br/>- Build, train, and validate machine learning models for prediction, classification, and clustering to support NBA use cases.<br/><br/>- Conduct exploratory data analysis (EDA) on both structured and unstructured data to extract actionable insights and identify behavioral drivers.<br/><br/>- Design and deploy A/B testing frameworks and build pipelines for model evaluation and continuous monitoring.<br/><br/>- Develop vectorization and embedding pipelines using models like Word2Vec, BERT, to enable semantic understanding and similarity search.<br/><br/>- Implement Retrieval-Augmented Generation (RAG) workflows to enrich recommendations by integrating internal and external knowledge bases.<br/><br/>- Collaborate with cross-functional teams (engineering, product, marketing) to deliver data-driven Next Best Action strategies.<br/><br/>- Present findings and recommendations clearly to technical and non-technical stakeholders.<br/><br/>Required Skills & Experience :<br/><br/>- Strong programming skills in Python, including libraries like pandas, NumPy, and scikit-learn.<br/><br/>- Practical experience with text vectorization and embedding generation (Word2Vec, BERT, SBERT, etc.).<br/><br/>- Proficiency in Prompt Engineering and hands-on experience in building RAG pipelines using LangChain, Haystack, or custom frameworks.<br/><br/>- Familiarity with vector databases (e.g., PostgreSQL with pgvector, FAISS, Pinecone, Weaviate).<br/><br/>- Expertise in Natural Language Processing (NLP) tasks such as NER, text classification, and topic modeling.<br/><br/>- Sound understanding of supervised learning, recommendation systems, and classification algorithms.<br/><br/>- Exposure to cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) is a plus.<br/><br/>Experience : 5+ years</p> (ref:hirist.tech)