Member of Technical Staff, Finance Research
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Job Description
Finance AI researcher developing benchmarks and evaluation frameworks for advanced financial reasoning and agentic systems. Conducting applied research across AI models, enterprise workflows, and quantitative finance.
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
- Translate research findings into measurable improvements in AI system performance
- Define methods for assessing financial intelligence across complex enterprise use cases
- Develop and curate datasets, test cases, and benchmark environments for enterprise finance challenges
- Translate ambiguous financial problems into measurable research questions and evaluation criteria
- Design assessment scenarios for complex financial reasoning and decision-making workflows
- Establish performance standards for finance-focused models and agentic systems
- Support repeatable and scientifically robust evaluation processes
- Analyse AI model behaviour, failure modes, reasoning patterns, and performance trends
- Identify weaknesses and improvement opportunities across finance-focused models and agentic workflows
- Develop methodologies for evaluating model performance across financial tasks
- Produce actionable research insights guiding experimentation and research priorities
- Incorporate emerging techniques from AI evaluation, machine learning, financial modelling, 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 materials
- Contribute to research standards for enterprise financial intelligence and AI evaluation
- Share findings with technical and finance-focused audiences
- Support a distributed research environment centred on scientific rigour, experimentation, and collaborative problem-solving
Requirements:
- Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a closely related discipline
- PhD strongly preferred
- MBA, CFA, or equivalent advanced professional expertise may also be considered
- Deep domain expertise in 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
- Experience producing research reports, technical documentation, or thought-leadership materials
- Experience working across research, engineering, product, and other cross-functional teams
- Proficiency with quantitative research and data-analysis tools such as Python, SQL, statistical-analysis environments, or machine-learning frameworks is advantageous
- Experience 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 advantageous
- Publication history in academic research, industry research, or recognised technical publications is beneficial
- Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
Benefits:
- Fully remote
- Full-time engagement
- Remote consulting opportunity
- Collaboration across research, engineering, product, and finance-focused stakeholders
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