Senior Data Scientist I

Overview

As a Senior Data Scientist I, you will help design and validate Agentic AI-driven capabilities within Protégé for PatentSight. You translate ML, NLP, and LLM techniques into scalable, customer-facing features. You will drive experiments, modeling, and evaluation in collaboration with engineers to deliver impactful IP workflows. This role sits at the intersection of data science and product, shaping how trusted patent data informs decisions. You’ll contribute to a culture of innovation and collaboration while tackling real-world IP analytics challenges.

Pay / Benefits

• generous holiday allowance
• private medical benefits
• pension scheme
• Save As You Earn share option scheme
• learning and development resources
• flexible working hours

Responsibilities

• Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompts, patent search).
• Define agentic workflows and reasoning strategies for multi-step IP tasks.
• Design retrieval strategies including hybrid search (semantic + lexical) and evaluation metrics.
• Analyze large-scale IP datasets to extract insights and improve model performance.
• Establish best practices for model evaluation, validation, and benchmarking.
• Translate experimental results into product recommendations with business impact.
• Collaborate with product, IP experts, and engineers to align solutions with user needs.

Key requirements

• Degree in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).
• Strong experience in machine learning, NLP, and LLM-based modeling.
• Experience designing and running experiments with 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 using embeddings and vector databases.
• Experience designing agentic workflows with hands-on exposure to agent frameworks (Google ADK, LangChain, LangGraph, AutoGen).
• Proficiency in data analysis tools and large-scale text processing.

• cross-functional collaboration
• problem-solving
• clear communication
• NLP
• LLMs
• machine learning

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