(Finance Research) Member of Technical Staff

About the role

Join our research team as a Member of Technical Staff (MTS), Finance Research, where you'll help define the frontier of AI-powered financial reasoning. This role sits at the intersection of large language models, agentic systems, and enterprise finance, with a focus on building rigorous evaluation frameworks that measure, benchmark, and advance AI performance across complex financial workflows.

Responsibilities

• Design, own, and evolve evaluation frameworks for AI agents operating in financial domains, including benchmark suites, scoring methodologies, quality rubrics, and research-grade evaluation protocols.
• Conduct original research on financial reasoning, decision-making, and workflow automation, translating findings into measurable improvements in AI system performance.
• Develop and curate datasets, test cases, and benchmark environments that capture real-world enterprise finance challenges.
• Collaborate with AI researchers, machine learning engineers, and product teams to evaluate, validate, and improve finance-focused models and agentic systems.
• Analyze model behavior, failure modes, and performance trends to generate actionable insights and guide research priorities.
• Publish internal research findings, technical reports, and best practices that contribute to the broader understanding of AI capabilities in finance.
• Help establish research standards and thought leadership for enterprise financial intelligence and AI evaluation.
• Foster a culture of scientific rigor, experimentation, and collaborative innovation within a distributed research environment.

Requirements

• Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a related field (PhD strongly preferred; MBA, CFA, or equivalent expertise also considered).
• Deep domain expertise in one or more areas of finance, including investment research, capital markets, risk management, corporate finance, accounting, or financial analysis.
• Demonstrated experience conducting rigorous research, developing analytical methodologies, or building evaluation frameworks in finance or related quantitative disciplines.
• Strong ability to translate ambiguous real-world financial problems into measurable research questions and evaluation criteria.
• Exceptional analytical and critical-thinking skills, with a track record of solving complex, multidisciplinary problems.
• Excellent written and verbal communication skills, including experience producing research reports, technical documentation, or thought leadership content.
• Experience working in highly collaborative, cross-functional environments involving research, engineering, and product stakeholders.

Preferred Qualifications

• Experience evaluating, benchmarking, or researching large language models, AI agents, reasoning systems, or enterprise AI applications.
• Familiarity with agentic workflows, AI evaluation methodologies, synthetic data generation, or model alignment techniques.
• Knowledge of contemporary research in machine learning, financial AI, decision intelligence, or computational finance.
• Experience designing industry benchmarks, assessment frameworks, or performance standards.
• Publication record in academic conferences, journals, industry research, or influential technical publications.
• Proficiency with data analysis, experimentation, or quantitative research tools (e.g., Python, SQL, statistical analysis, or machine learning frameworks).