About this role
Role Overview
We are seeking a Data Scientist to bridge the gap between intellectual property (IP) strategy and financial performance for the Legal Patents business. You will manage patent portfolio analytics, working with legal, finance, and market data to transform raw patent data and financial metrics into actionable insights that drive high-stakes negotiations and long-term corporate strategy.
This role requires a Data Scientist who can operate across the full analytics lifecycle: translating ambiguous business questions into measurable problems, identifying and preparing the right data, developing statistically sound models, validating results, and partnering with engineering teams to deliver trusted data products.
Core Responsibilities
Data Analysis & Portfolio Intelligence Analyze financial and patent activity data to identify trends, risks, high-value assets, underutilized IP, and cost-saving opportunities Develop and maintain dashboards and reports to communicate findings to stakeholders and leadership Data Collaboration Partner with Data Engineering teams to identify, evaluate, and ingest new data sources such as global litigation trends, competitor filing activities, and market valuation metrics Ensure data quality and integrity for all analyses Build reliable, repeatable, and scalable workflows that contribute to data validation, feature engineering, model deployment to ensure outputs are production ready Decision Support Provide data-driven recommendations to leadership for patent portfolio strategy, R&D investments, IP protection, and financial planning Develop predictive models to forecast portfolio performance and value Deal Simulation & Negotiation Support Build and run simulations of potential deal structures (licensing, acquisitions, divestitures) to inform negotiation strategies Present analysis and scenarios to support decision-making during complex negotiations Apply sound statistical methods to validate assumptions, measure model performance, and communicate confidence levels, limitations, and trade-offs to stakeholders Cross-functional Collaboration Work with legal, finance, and R&D teams to align data analysis with business objectives and patent strategy Advanced Analytics Apply machine learning, natural language processing (NLP), embeddings, classification, clustering, and LLM-based techniques to categorize patent claims, assess patent quality, and forecast industry trends
Qualifications & Technical Skills Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, or a related field At least 2 years of work experience in a data science role Proficiency in Python, R, or similar languages for data analysis and modelling Experience with SQL and data visualization tools (e.g., Tableau, Power BI) Familiarity with statistical methods, machine learning, and predictive modeling
Preferred Skills & Experience Proven experience working with Intellectual Property (IP) data (e.g., USPTO/EPO datasets) or financial analytics within a corporate setting Familiarity with NLP techniques for analysing legal text and patent claims Prior experience collaborating with Data Engineers to build and maintain ETL pipelines Experience with Databricks, Spark, Delta Lake, and or cloud-based platforms Experience with CI/CD, Git-based development workflows, automated testing and production deployment practices
Business Acumen Basic understanding of financial analysis and patent/IP concepts is a plus Strong analytical and problem-solving skills
Soft Skills & Schedule Requirements Excellent communication and collaboration abilities Detail-oriented with a focus on delivering actionable insights
Schedule Requirements Must be available to work US California hours (Pacific Time) through at least 11:00 AM PT on business days