Job details
About this role
Role overview
This role leads strategic finance pilots and research initiatives that produce training and evaluation data for financial AI models. The position sits at the intersection of customer goals, financial domain expertise, and large-scale delivery operations, taking projects from initial scoping through to operational launch. It is a hands-on leadership role focused on turning emerging financial AI use cases into validated, repeatable programs.
Responsibilities
- Own end-to-end delivery of frontier financial AI pilots, from scoping and design through to operationalization and scale-up - Define financial quality, feasibility, and cost standards that determine whether a pilot is fit for production - Shape how market data, financial statements, regulatory filings, disclosures, and quantitative or risk models are applied within AI training and evaluation workflows - Convert pilots into scalable projects by documenting workflows, expert staffing models, and quality benchmarks - Partner closely with researchers and global delivery teams to align technical requirements with operational execution - Serve as the bridge between customer objectives and financial domain knowledge, translating between stakeholders
Requirements
- Strong academic or professional background in finance, financial engineering, economics, or accounting - At least two years leading complex projects, operational workflows, or finance-focused initiatives - Working depth in financial data, markets, accounting, or modeling, with the judgment to assess when a dataset is fit for purpose - Comfort operating at pace in a high-intensity, fast-changing environment with an entrepreneurial mindset
Nice to have
- Experience with AI or machine learning companies, AI research labs, or data annotation and evaluation projects - Track record managing finance-oriented, technical, or data-intensive projects - Familiarity with data pipelines, AI training workflows, model evaluation processes, or human-in-the-loop operations
Benefits and work setup
- Flexibility to structure delivery in a way that suits both the individual and their team - Access to tools, resources, and ongoing development opportunities to build capability over time - A collaborative culture that values curiosity, accountability, humility, and a commitment to high-quality outcomes - Exposure to complex challenges that shape AI development across industries and geographies