Senior Data Scientist II

Responsibilities

• Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).
• Define agentic workflows and reasoning strategies for multi-step legal tasks.
• Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).
• Analyze large-scale legal datasets to extract insights and improve model performance.
• Establish best practices for model evaluation, validation, and benchmarking.
• Translate experimental results into clear product recommendations and business impact.
• Collaborate with product, legal experts, and engineers to align solutions with user needs.
• Mentor team members and provide technical leadership in data science and AI.

• Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.)
• Strong experience in machine learning, NLP, and LLM-based modeling
• Strong experience designing and running experiments, including model evaluation and iteration
• Strong coding skills
• Experience with generative AI techniques (e.g., prompt engineering, RAG)
• Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases
• Experience designing agentic workflows and reasoning strategies, with hands‑on experience applying agent frameworks (e.g., Lang Chain, Lang Graph, Auto Gen) in real‑world use cases
• Proficiency in Python and data analysis tools
• Strong foundation in statistics, modeling, and large‑scale text processing

Demonstrates expertise in Natural Language Processing (NLP), Large Language Models (LLM), and generative AI techniques, with a strong foundation in machine learning and statistical analysis. Capable of designing agentic workflows and hybrid search strategies while providing technical leadership and mentoring in data science.

• Lang Chain
• Lang Graph
• Auto Gen
• Vector Databases