Job Description
Thomson Reuters is expanding its Data Science and AI organization and is looking for a Manager to lead a team building intelligent products and automation. You will own the full lifecycle of ML and GenAI solutions, from problem framing to production deployment and operation. The work spans traditional machine learning and modern GenAI systems, including LLM applications, RAG, agents, and multi-agent platforms. You will set technical direction, develop your team, and partner with business stakeholders to deliver measurable impact.
Key Responsibilities
Production deployment and delivery
- Own end-to-end delivery of ML and GenAI solutions from prototype to monitored production systems.
- Establish MLOps and LLMOps practices: CI/CD, versioning, testing, observability, drift detection, and cost monitoring.
- Define evaluation frameworks for both classical models and LLM/agent systems, covering accuracy, groundedness, safety, and regression testing.
Technical platform ownership
- Own the architecture, roadmap, and operations of the team's AI platform, including model serving, vector stores, retrieval pipelines, and orchestration layers.
- Build reusable agentic capabilities (tools, skills, workflow templates, evaluation harnesses) for adoption across teams and products.
- Lead build-versus-buy decisions across models, frameworks, and cloud services.
Technical thought leadership
- Set direction for agentic AI, RAG, and multi-agent orchestration, and define architecture patterns and standards.
- Evaluate emerging models, frameworks, and protocols (e.g., MCP) and translate them into practical adoption.
- Champion responsible AI, security, and governance in all solutions.
Coaching and mentoring
- Lead, coach, and grow data scientists and AI engineers through feedback, code and design reviews, and career development.
- Build a culture of rigor, experimentation, and ownership.
- Hire, onboard, and retain strong talent.
Stakeholder partnership
- Partner with Sales, Marketing, Product, and Operations to prioritize use cases and design solutions.
- Apply AI and data science to business problems such as workflow automation, customer retention, cross-sell, segmentation, pricing, and recommendations.
- Communicate results and trade-offs clearly to audiences from engineers to senior leadership.
Required Qualifications
- 8-10 years of experience in data science and machine learning, with models deployed in production.
- Experience leading, mentoring, or managing data scientists or ML engineers.
- Hands-on experience building LLM applications, including prompt engineering, RAG, embeddings, and vector search.
- Experience designing and shipping agentic systems, including tool use, orchestration, and agent evaluation.
- Strong foundation in statistics, machine learning, and hypothesis testing.
- Expert Python and strong SQL skills.
- Experience with scikit-learn, PyTorch, or TensorFlow.
- Experience with cloud platforms (preferably AWS), containerization, and CI/CD for model deployment.
- Experience applying ML to business problems such as predictive analytics, segmentation, pricing, or recommendations.
- Strong communication and stakeholder management skills.
- Bachelor's degree or higher; a quantitative field is preferred.
Preferred Qualifications
- Experience building multi-agent platforms with frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
- Experience with MCP and building reusable tools and skills for agents.
- Experience with LLMOps tooling, including tracing, evaluation, guardrails, and prompt management.
- Experience with advanced RAG techniques such as hybrid search, re-ranking, and retrieval evaluation.
- Familiarity with responsible AI practices, including hallucination mitigation, privacy, and governance.
- Experience on sales, marketing, or revenue-operations data, or automating business workflows with AI.
- Experience owning an AI platform used by multiple teams.
#LI-NG1
What’s in it For You?
Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
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.
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. More information on requesting an accommodation here.
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More information about Thomson Reuters can be found on thomsonreuters.com.
Skills Required
- 8-10 years of experience in data science and machine learning, including production model deployment
- Experience leading, mentoring, or managing data scientists or ML engineers
- Hands-on experience building LLM applications using prompt engineering, RAG, embeddings, and vector search
- Experience designing and shipping agentic systems with tool use, orchestration, and agent evaluation
- Strong foundation in statistics, machine learning, and hypothesis testing
- Expert Python skills
- Strong SQL skills
- Experience with scikit-learn, PyTorch, or TensorFlow
- Experience with cloud platforms, preferably AWS
- Experience with containerization and CI/CD for model deployment
- Experience applying machine learning to predictive analytics, segmentation, pricing, or recommendations
- Strong communication and stakeholder management skills
- Bachelor's degree or higher
- Quantitative academic field
- Experience building multi-agent platforms with LangChain, LangGraph, CrewAI, or AutoGen
- Experience with MCP and reusable tools and skills for agents
- Experience with LLMOps tooling, including tracing, evaluation, guardrails, and prompt management
- Experience with advanced RAG techniques, including hybrid search, re-ranking, and retrieval evaluation
- Familiarity with responsible AI practices, hallucination mitigation, privacy, and governance
- Experience with sales, marketing, or revenue-operations data, or AI-based business workflow automation
- Experience owning an AI platform used by multiple teams
Thomson Reuters Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Thomson Reuters and has not been reviewed or approved by Thomson Reuters.
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Flexible Benefits — Flexible work options such as hybrid schedules and “Flex My Way” with Work From Anywhere allowances (including limited weeks abroad) are offered and positioned to support work-life balance. Feedback suggests policy-backed flexibility is a notable strength even though application can vary by role and manager.
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Leave & Time Off Breadth — Generous paid time off, enhanced bereavement, caregiver leave, two global mental-health days, and a sabbatical program expand time-away options. Paid parental leave is explicitly highlighted, with a global minimum described at 16 weeks.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with wellbeing resources such as EAP, mental-health tools, and fitness/wellbeing programs. FSAs/HSAs and related health benefits reinforce the depth of the healthcare offering.
Thomson Reuters Insights
What We Do
Thomson Reuters (NYSE / TSX: TRI) informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. The company serves professionals across legal, tax, accounting, compliance, government, and media. Its 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. For more information, visit tr.com.
