Member of Technical Staff, Finance Research

This is a fully remote position, open to applicants in New York.

📋 Description

• Create, develop, and enhance evaluation frameworks for AI systems functioning within financial sectors.

• Construct benchmark suites, scoring methodologies, quality assessment rubrics, and research-grade evaluation protocols.

• Execute applied research in financial reasoning, decision-making, and workflow automation.

• Convert research outcomes into quantifiable enhancements in AI system performance.

• Establish methods for evaluating financial intelligence across intricate enterprise scenarios.

• Generate and manage datasets, test cases, and benchmark environments tailored for enterprise finance challenges.

• Interpret vague financial issues into quantifiable research inquiries and evaluation standards.

• Design evaluation scenarios for intricate financial reasoning and decision-making processes.

• Set performance benchmarks for finance-oriented models and agentic systems.

• Facilitate repeatable and scientifically robust evaluation methodologies.

• Analyze AI model behavior, failure modes, reasoning patterns, and performance trends.

• Identify vulnerabilities and opportunities for enhancement within finance-centric models and agentic workflows.

• Develop strategies for assessing model performance across various financial tasks.

• Generate actionable research insights that inform experimentation and research priorities.

• Integrate innovative techniques from AI evaluation, machine learning, financial modeling, and agent architectures.

• Collaborate with AI researchers, machine learning engineers, product professionals, and research stakeholders.

• Produce internal research reports, technical documentation, methodological guidance, and best-practice resources.

• Contribute to research standards for enterprise financial intelligence and AI evaluation.

• Present findings to both technical and finance-oriented audiences.

• Foster a distributed research environment focused on scientific rigor, experimentation, and collaborative problem-solving.

⛳️ Requirements

• Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a related field is required.

• A PhD is strongly preferred.

• An MBA, CFA, or equivalent advanced professional qualifications may also be considered.

• Extensive domain knowledge in investment research, capital markets, risk management, corporate finance, accounting, or financial analysis.

• Proven experience in conducting thorough research, developing analytical methodologies, or creating evaluation frameworks.

• Ability to transform complex or ambiguous financial challenges into measurable research queries and assessment criteria.

• Outstanding analytical, quantitative, and critical-thinking abilities.

• Exceptional written and verbal communication skills.

• Experience in producing research reports, technical documentation, or thought-leadership content.

• Background in collaborating across research, engineering, product, and other cross-functional teams.

• Proficiency in quantitative research and data analysis tools such as Python, SQL, statistical analysis environments, or machine learning frameworks is a plus.

• Experience in evaluating or benchmarking large language models, AI agents, reasoning systems, or enterprise AI applications is advantageous.

• Familiarity with agentic workflows, synthetic data generation, AI evaluation methodologies, or model-alignment techniques is beneficial.

• A record of publications in academic research, industry research, or recognized technical journals is a plus.

• All work must be carried out without the use of confidential or proprietary information belonging to any employer, client, institution, or other third parties.

🏝️ Benefits

• Fully remote work environment.

• Full-time engagement opportunity.

• Remote consulting options available.

• Collaboration with research, engineering, product, and finance-oriented stakeholders.