Senior Data Scientist

Job title: Senior Data Scientist
Vendor Rate: Experience: 6 to 8 yrs

Role is onsite - Hybrid (3 days in office)

Location: Raleigh NC

Job Summary: The Senior Data Scientist will coordinate complex cloud and artificial intelligence initiatives that leverage large language models and advanced machine learning within a hybrid work model. The role will orchestrate projects across AWS GCP or Azure environments ensuring reliable Python based solutions that apply frameworks such as Keras spaCy and PyTorch to deliver measurable value for clients and communities.

Required Skills: Python PyTorch Machine Learning Prompt Engineering Large Language Models AWS / GCP / Azure Cloud

Responsibilities: Develop and implement LLM based applications tailored for in house legal needs ensuring they align with Cognizants commitment to excellence and innovation Evaluate and maintain our data assets and training evaluation datasets ensuring they meet the highest standards of integrity and quality. Design and build pipelines for preprocessing annotating and managing legal document datasets fostering a customer centric mindset. Collaborate with legal experts to understand requirements and ensure models meet domain specific needs working as one team. Conduct experiments and evaluate model performance to drive continuous improvements raising the bar in all deliverables. Evaluate AI ML and GenAI outcomes both human and automated to ensure accuracy reliability and alignment with business objectives. Interface with other technical personnel or team members to finalize requirements demonstrating ownership of outcomes. Work closely with other development team members to understand complex product requirements and translate them into software designs ensuring ethical choices in all actions. Successfully implement development processes coding best practices and code reviews for production environments embodying Cognizant s values in every task. Strong hands on experience and foundations in machine learning including dimensionality reduction clustering embeddings and sequence classification algorithms. Experience with deep learning frameworks such as PyTorch TensorFlow and Hugging Face Transformers. Practical experience in Natural Language Processing methods and libraries such as spaCy word2vec TensorFlow Keras PyTorch Flair BERT. Practical experience with large language models prompt engineering fine tuning and benchmarking using frameworks such as LangChain and LlamaIndex. Strong Python background. Knowledge of AWS GCP Azure or other cloud platforms. Understanding of data modelling principles and complex data models. Proficiency with relational and NoSQL databases as well as vector stores e.g Postgres Elasticsearch OpenSearch ChromaDB. Knowledge of Scala Spark Ray or other distributed computing systems is highly preferred. Knowledge of API development containerization and machine learning deployment is highly preferred. Experience with ML Ops AI Ops is highly preferred. nal environments where programs span different regions cultures and regulatory contexts within a day shift structure