We are sharing a specialised full-time opportunity for finance research professionals with deep expertise in financial analysis, quantitative research, enterprise finance, or related disciplines to contribute to advanced research at the intersection of AI, financial reasoning, and agentic systems.
Selected professionals will conduct applied research, develop rigorous evaluation methodologies, and help define how advanced AI systems are assessed across complex financial workflows. The work combines financial domain expertise with benchmarking, experimentation, model evaluation, and cross-functional research collaboration.
Key Responsibilities
Financial AI Research & Evaluation
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Design, develop, and evolve evaluation frameworks for AI systems operating across financial domains
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Build benchmark suites, scoring methodologies, quality rubrics, and research-grade evaluation protocols
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Conduct applied research into financial reasoning, decision-making, and workflow automation
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Translate research findings into measurable improvements in AI system performance
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Define rigorous methods for assessing financial intelligence across complex enterprise use cases
Benchmarking & Dataset Development
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Develop and curate datasets, test cases, and benchmark environments representing real-world enterprise finance challenges
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Translate ambiguous financial problems into measurable research questions and evaluation criteria
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Design assessment scenarios covering complex financial reasoning and decision-making workflows
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Establish appropriate performance standards for finance-focused models and agentic systems
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Support the development of repeatable and scientifically robust evaluation processes
Model Analysis & Research Methodology
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Analyse AI model behaviour, failure modes, reasoning patterns, and performance trends
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Identify weaknesses and opportunities for improvement across finance-focused models and agentic workflows
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Develop analytical methodologies for evaluating model performance across financial tasks
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Produce actionable research insights that can guide future experimentation and research priorities
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Incorporate emerging techniques from AI evaluation, machine learning, financial modelling, and agent architectures into research initiatives
Cross-Functional Research & Thought Leadership
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Collaborate closely with AI researchers, machine learning engineers, product professionals, and other research stakeholders
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Produce internal research reports, technical documentation, methodological guidance, and best-practice materials
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Contribute to research standards for enterprise financial intelligence and AI evaluation
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Share findings clearly with both technical and finance-focused audiences
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Support a distributed research environment centred on scientific rigour, experimentation, and collaborative problem-solving
Ideal Profile
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Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a closely related discipline, with a PhD strongly preferred
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MBA, CFA, or equivalent advanced professional expertise may also be considered
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Deep domain expertise in one or more areas including investment research, capital markets, risk management, corporate finance, accounting, or financial analysis
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Demonstrated experience conducting rigorous research, developing analytical methodologies, or building evaluation frameworks
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Strong ability to convert complex or ambiguous financial problems into measurable research questions and assessment criteria
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Exceptional analytical, quantitative, and critical-thinking skills
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Excellent written and verbal communication skills, including experience producing research reports, technical documentation, or thought-leadership materials
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Experience working across research, engineering, product, and other cross-functional teams
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Experience evaluating or benchmarking large language models, AI agents, reasoning systems, or enterprise AI applications is advantageous
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Familiarity with agentic workflows, synthetic data generation, AI evaluation methodologies, or model-alignment techniques is advantageous
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Publication history in academic research, industry research, or recognised technical publications is beneficial
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Proficiency with quantitative research and data-analysis tools such as Python, SQL, statistical-analysis environments, or machine-learning frameworks is advantageous
Engagement Details
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Full-time engagement
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Fully remote
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Research-focused role spanning financial AI, benchmarking, evaluation, and agentic finance workflows
- Compensation: $400,000–$800,000/year
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Work will involve applied research, evaluation-framework development, benchmark design, model analysis, and technical documentation
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Collaboration will take place across research, engineering, product, and finance-focused stakeholders
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Role scope, research priorities, and responsibilities may evolve as project requirements develop
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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