Data Scientist

Role Summary

The Lead Data Scientist will act as a technical leader and consultant, guiding clients through the complete data-to-insights lifecycle to solve real-world problems using advanced Generative AI (GenAI) and Natural Language Processing (NLP). The role involves hands-on

model creation, strategic client engagement, and ensuring the delivery of innovative, high-impact solutions leveraging textual data.

Key Responsibilities

• Client & Strategy: Understand complex business problems and translate them into actionable, innovative AI/ML solutions in a consultative mindset for client stakeholders.

• GenAI & LLM Implementation: Lead the creation, experimentation, and delivery of solutions leveraging the latest GenAI models (LLMs) such as Mistral, Falcon, Llama 2, GPT 3.5 & 4, with proficiency in Prompt Engineering.

• NLP & Deep Learning: Design and implement advanced NLP/NLG/NLU applications using popular deep learning frameworks and models, including PyTorch, TensorFlow, BERT, and Langchain.

• Semantic Modeling: Must have hands-on experience with Semantic Modeling and Named Entity Recognition (NER), along with expert-level understanding of language semantic concepts and data standardization.

• End-to-End Delivery: Own the project lifecycle from initiation to business impact creation, ensuring successful integration of NLP models into client business workflows.

• Advanced Analytics: Perform exploratory, Machine Learning, and Advanced Analytics on textual data, applying techniques like Forecasting, Text Mining, and Linear/Logistic Regression.

Required Qualifications & Skills

Technical Expertise

• Experience: Total 5+ years of professional experience using analytical tools/languages like Python on large-scale data.

• NLP/LLM: Strong practical experience in NLP/NLG/NLU applications, working with pre-trained models, and awareness of state-of-the-art embeddings and their applicability.

• Frameworks & Tools (Must Have):

Deep Learning Frameworks: PyTorch or TensorFlow.

LLM Libraries/Models: BERT, Langchain, GPT (or similar models).

Coding: Python and SQL.

• Advanced Concepts: Expert/high-level understanding of language semantic concepts, data standardization, and semantic modeling.

• Cloud (Plus): Exposure to Azure services for ML & GenAI projects is a strong plus.Role & responsibilities