Remote | Member of Technical Staff, Finance Research — $400,000–$800,000/year

24-Mag•New York, NY

1d•Remote

About The Position

This full-time, fully remote, research-focused role applies financial domain expertise to AI research, evaluation, and agentic finance workflows. The professional will design evaluation frameworks and benchmark suites, develop datasets and assessment scenarios, study model behavior, and translate findings into measurable improvements in AI systems used for complex financial workflows. The position involves applied research, experimentation, methodology development, technical documentation, and collaboration with research, engineering, product, and finance-focused stakeholders. Role scope, research priorities, and responsibilities may evolve as project requirements develop. Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party. The opportunity is available through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

Requirements

Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a closely related discipline; a PhD is strongly preferred. An MBA, CFA, or equivalent advanced professional expertise may also be considered.
Deep expertise in one or more areas 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.
Ability to convert complex or ambiguous financial problems into measurable research questions and assessment criteria.
Exceptional analytical, quantitative, and critical-thinking skills.
Excellent written and verbal communication skills, including experience producing research reports, technical documentation, or thought-leadership materials.
Experience working across research, engineering, product, and other cross-functional teams.

Nice To Haves

Experience evaluating or benchmarking large language models, AI agents, reasoning systems, or enterprise AI applications.
Familiarity with agentic workflows, synthetic data generation, AI evaluation methodologies, or model-alignment techniques.
Publication history in academic research, industry research, or recognised technical publications.
Proficiency with quantitative research and data-analysis tools such as Python, SQL, statistical-analysis environments, or machine-learning frameworks.

Responsibilities

Design, develop, and evolve evaluation frameworks for AI systems operating across financial domains.
Build benchmark suites, scoring methodologies, quality rubrics, and research-grade evaluation protocols.
Conduct applied research into financial reasoning, decision-making, and workflow automation, and translate findings into measurable improvements in AI system performance.
Define rigorous methods for assessing financial intelligence across complex enterprise use cases.
Develop and curate datasets, test cases, and benchmark environments representing real-world enterprise finance challenges.
Translate ambiguous financial problems into measurable research questions, evaluation criteria, and assessment scenarios.
Establish performance standards for finance-focused models and agentic systems and support repeatable, scientifically robust evaluation processes.
Analyze AI model behavior, failure modes, reasoning patterns, and performance trends.
Identify weaknesses and opportunities for improvement across finance-focused models and agentic workflows.
Develop analytical methodologies for evaluating model performance across financial tasks and produce actionable research insights.
Incorporate emerging techniques from AI evaluation, machine learning, financial modelling, and agent architectures into research initiatives.
Collaborate with AI researchers, machine learning engineers, product professionals, and other research stakeholders.
Produce internal research reports, technical documentation, methodological guidance, and best-practice materials.
Contribute to research standards for enterprise financial intelligence and AI evaluation.
Communicate findings to technical and finance-focused audiences and support a distributed research environment centred on scientific rigour, experimentation, and collaborative problem-solving.