# Applied Science Leader - AI Solutions for Tax and Accounting

**Company**: Thomson Reuters
**Location**: New York, New York
**Experience**: senior
**Job type**: full-time
**Salary**: $198,200 USD - $368,000 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://thomsonreuters.wd5.myworkdayjobs.com/en-US/External_Career_Site/job/United-States-of-America-New-York-New-York/Senior-Director--Applied-Research_JREQ199086-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_f68db8a9-54a

## Description

Thomson Reuters Labs is seeking an experienced applied science leader with a strong product mindset to lead a high-performing team developing transformative AI solutions for tax, audit, and accounting professionals.

You will lead applied research and development for the next generation of agentic AI capabilities supporting tax and accounting professionals around the world. You will help create entirely new workflows that address fundamental challenges across the industry.

**Responsibilities:**

- Lead and develop a high-performing applied science team focused on agentic AI solutions for tax and accounting professionals.

- Drive the design, development, and delivery of AI features that meaningfully reimagine customer workflows in high-stakes, accuracy-critical settings.

- Set technical direction for applied research initiatives, balancing scientific rigor, customer value, product feasibility, and delivery timelines.

- Partner closely with product engineering teams to transition research innovations into scalable, reliable, production-ready capabilities.

- Serve as a strategic thought partner to Labs leadership, product leadership, and key business stakeholders on long-term AI strategy, external partnerships, and capability roadmaps.

- Influence product strategy through deep technical expertise and insights derived from product usage data, quality metrics, evaluations, and customer feedback.

- Develop and advance approaches for LLM-based systems, agentic workflows, information retrieval, document understanding, knowledge representation, and AI evaluation.

- Ensure AI systems are designed with appropriate accuracy, verification, observability, safety, and quality controls for professional tax and accounting use cases.

- Engage tax, audit, accounting, and other subject-matter experts in concept development, design workshops, experimentation, and solution validation.

- Continuously improve ways of working across R&D and product engineering in a fast-paced, tightly embedded delivery environment.

- Foster a culture of innovation, rigor, collaboration, technical excellence, and continuous learning across the team.

- Represent TR Labs and the broader tax technology organization in internal technical forums, cross-functional initiatives, and relevant external research communities.

**Requirements:**

- PhD in Computer Science, Machine Learning, or a closely related field; or a Master's degree with equivalent depth, a strong scientific background, and a relevant publication record.

- 10+ years of hands-on industry experience building AI and machine learning systems for commercial applications; research-only experience is not sufficient.

- Recent, direct hands-on experience developing LLM-based and agentic AI systems for production, non-trivial use cases.

- 5+ years of experience managing and developing high-performing applied science, machine learning, or AI research teams.

- Demonstrated success in product-facing or customer-facing roles, with measurable business and customer impact as the primary measure of success.

- Technical depth in AI and machine learning sufficient to challenge assumptions, expand upon team ideas, guide high-quality technical decisions, and establish effective research direction.

- Strong expertise in information retrieval and natural language processing, particularly in complex vertical domains.

- Experience with one or more of the following: taxonomy induction, document understanding, agentic search, knowledge graphs, neuro-symbolic AI, or comparable approaches for complex knowledge-intensive workflows.

- Experience evaluating AI agents and language-model-based systems, including approaches involving verifiable rewards, synthetic data generation, and rigorous quality measurement.

- A relevant publication record, including publications at ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, KDD, or equivalent venues.

- Experience building AI solutions for tax, legal, audit, accounting, or other highly regulated and knowledge-intensive domains.

- A demonstrated track record of growth and leadership at top-tier technology companies, high-growth startups, or similarly demanding environments.

- Strong communication and influencing skills, with the ability to work effectively with applied scientists, engineers, product leaders, domain experts, and senior business stakeholders.

- A passion for developing people, building strong teams, and creating an inclusive, high-performing culture.

**Benefits:**

- Flexibility & Work-Life Balance: Flex My Way supportive workplace policies, flexible work arrangements, including work from anywhere for up to 8 weeks per year.

- Career Development and Growth: Grow My Way programming and skills-first approach.

- Industry Competitive Benefits: Comprehensive benefit plans, flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs.

- Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance.

- Social Impact: Social Impact Institute, two paid volunteer days off annually, opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.

- Making a Real-World Impact: Helping customers pursue justice, truth, and transparency.

**Salary Range:** $198,200 USD - $368,000 USD

## Skills

### Required
- AI
- Machine Learning
- LLM-based systems
- Agentic AI
- Information Retrieval
- Natural Language Processing

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