Data Scientist Text Analytics & GenAI

Role Overview: As a Lead Data Scientist specializing in Text Analytics & GenAI, you will be responsible for designing and implementing cutting-edge solutions to convert unstructured textual data into actionable insights. Collaborating with different teams and clients, you will be applying NLP, NLU, and Generative AI techniques to address a variety of real-world challenges. Key Responsibilities: - Collaborate with business and technical stakeholders to create data-driven solutions using text and language data. - Develop NLP/NLG/NLU models for semantic understanding, entity recognition, and text summarization. - Experiment with and optimize pre-trained LLMs and embedding models like GPT, Llama 2, Falcon, and Mistral. - Build scalable pipelines for data processing, model training, and deployment. - Utilize machine learning and deep learning methods to extract insights from extensive textual datasets. - Integrate AI models into business processes to generate measurable outcomes. - Stay updated with the latest advancements in Text Analytics, LLMs, and GenAI tools and frameworks. Qualifications Required: - Minimum 4 years of experience working with Python and analytical tools on large datasets. - Proficiency in Semantic Models and Named Entity Recognition (NER). - Hands-on experience in NLP/NLU/NLG using PyTorch, TensorFlow, BERT, LangChain, and OpenCV. - Exposure to GenAI models such as GPT 3.5/4, Llama 2, Mistral, Falcon, and Prompt Engineering. - Familiarity with Azure ML or other cloud-based AI/ML services. - Strong understanding of ML algorithms including Linear/Logistic Regression, Decision Trees, Clustering, Text Mining, Forecasting, and Optimization. - Proficient in programming and data skills with Python, SQL, and ML frameworks like TensorFlow. - Demonstrated capability to engage clients, transform issues into AI solutions, and deliver tangible business results. - High-level comprehension of language semantics and data standardization principles.,