W2 - Senior Data Scientist

Job title:
Senior Data Scientist

Role is onsite - Hybrid (3 days in office)

Location:
Raleigh, NC

W2 Only

6-12 Months contract

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.

• Develop and implement LLM-based applications tailored for in‑house legal needs, ensuring alignment with organizational excellence and innovation.
• Evaluate and maintain data assets and training evaluation datasets, ensuring 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 a cohesive 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.
• Translate complex product requirements into software designs, ensuring ethical choices in all actions.
• Implement development processes, coding best practices, and code reviews for production environments, embodying company values.

• 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, Tensor Flow, and Hugging Face Transformers.
• Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, Tensor Flow, Keras, Flair, and BERT.
• Practical experience with large language models, prompt engineering, fine‑tuning, and benchmarking using frameworks such as Lang Chain and Llama Index.
• Strong Python background; proficiency with relational and No
  
  SQL databases as well as vector stores (e.g., Postgres, Elasticsearch, Open Search, ChromaDB).
• Knowledge of AWS, GCP, Azure, or other cloud platforms.
• Understanding of data modeling principles and complex data models.
• 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 and AI Ops is highly preferred.
• Required Skills:
  
  Python, PyTorch, Machine Learning, Prompt Engineering, Large Language Models, AWS / GCP / Azure Cloud.