Senior Data Scientist

Responsibilities

• Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search).
• Define agentic workflows and reasoning strategies for multi-step IP tasks.
• Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).
• Analyse large-scale IP 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, IP experts, and engineers to align solutions with user needs.

• Degree 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 in Python.
• 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., Google ADK, Lang Chain, Lang Graph, Auto Gen) in real-world use cases.
• Proficiency in data analysis tools.
• Strong foundation in statistics, modeling, and large-scale text processing.

Demonstrates expertise in developing and implementing NLP, LLM, and generative AI approaches, with a strong foundation in machine learning and data analysis. Proficient in designing agentic workflows and hybrid search strategies to enhance model performance and deliver actionable insights.

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