Lead Applied Scientist

Lead Applied Scientist Thomson Reuters is seeking a Lead Applied Scientist. This is where emergent intelligence meets real-world impact. You'll work at the cutting edge of GenAI and machine learning agents, building systems that combine neural and symbolic reasoning, understand multiple modalities, and personalize themselves to individual users and evolving contexts. Your work will transform how millions of legal, tax, and compliance professionals interact with information—not through static tools, but through intelligent agents that understand their domain, anticipate their needs, and evolve with their workflows. About the Role Design and deploy neuro-symbolic AI systems that seamlessly integrate neural learning with structured knowledge representation and ontologies Build multi‑modal models that synthesize insights across text, documents, structured data, and domain‑specific artifacts Explore the emergent intelligence at the intersection of GenAI and machine learning agents, creating autonomous systems that reason and act Develop adaptive domain‑specific reasoning capabilities that understand the nuances of legal, regulatory, and financial contexts Own and lead end‑to‑end research deliverables—from ideation and experimentation to production deployment Establish comprehensive AI evaluation frameworks, quality assessment methodologies, and observability systems that ensure reliability, fairness, and transparency Leverage advanced information retrieval techniques, prompting workflows, and model training strategies to optimize solutions Shape long‑term AI strategy by providing strategic input to business and Labs leadership Champion AI personalization and continual learning approaches that make products smarter with every interaction Lead stakeholder engagement across UX, Product, and Engineering teams to align AI capabilities with user needs Develop in‑depth knowledge of customer problems and data Mentor scientists and engineers on best practices in applied AI research and production ML systems Build expertise in knowledge representation, domain reasoning, and agentic AI architectures Foster a culture that balances scientific rigor with pragmatic delivery and customer value About You PhD in Computer Science, Machine Learning, AI, or related field (or Master’s with equivalent depth of experience) 7+ years building production IR/NLP systems for commercial applications with demonstrated business impact Strong software engineering capabilities with experience in production code, MLOps, and managed delivery pipelines Proven track record translating complex, ambiguous problems into successful AI applications Proficiency in AI evaluation, quality assessment, and observability for production systems Neuro‑symbolic AI architectures that combine learning and reasoning Expertise in multi‑modal modeling across diverse data types and representation formats Hands‑on experience with knowledge representation, ontologies, and semantic reasoning systems Track record implementing AI personalization and continual learning that adapts to user behavior and feedback Experience with adaptive domain‑specific reasoning in specialized professional contexts Familiarity with emergent intelligence at the intersection of GenAI and machine learning agents—including agentic frameworks, tool use, and autonomous decision‑making Demonstrated ability to scale impact through others in applied research or advanced development settings Outstanding communication skills—you translate complex technical concepts for diverse audiences Proven success collaborating with Product, Engineering, and Business stakeholders in agile environments Strong problem‑solving and analytical thinking with a bias toward action and iteration What’s in it For You? Flexibility & Work‑Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work‑life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real‑world solutions. Our Grow My Way programming and skills‑first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI‑enabled future. Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company‑wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing. Culture: Globally recognized, award‑winning reputation for inclusion and belonging, flexibility, work‑life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro‑bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real‑World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations. For Ontario, Canada, the base compensation range for this role is $140,000 CAD - $175,000 CAD. Base pay is positioned within the range based on several factors including an individual’s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs. This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance. About Us Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug‑free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. #J-18808-Ljbffr