Finance Expert Lead, Gemini Data, DeepMind

Overview

As Finance Expert Lead, you will shape DeepMind Gemini’s data strategy for finance by mapping workflows, prioritizing capabilities, and curating high-quality data. You’ll collaborate with research to close gaps in data coverage and sourcing pipelines, and design tasks, rubrics, and QA for datasets from vendors, customers, and synthetic sources. You will drive data priorities based on model failures and benchmarks, and guide cross-team evaluations to ensure domain realism. You’ll recruit and mentor SMEs, enforce vendor quality, and turn expert contributions into training and evaluation data.

Pay / Benefits

• 20% bonus target
• equity
• benefits

Responsibilities

• Map Finance workflows into a use-case taxonomy and align with research priorities for capabilities, data coverage, and sourcing pipelines
• Design tasks and rubrics and implement QA for datasets from vendors, customers, and synthetic pipelines to ensure correctness and realism
• Steer data priorities by reproducing model failures and stress-testing on real workflows to uncover domain knowledge gaps, conventions issues, and incorrect assumptions
• Build Finance evaluations by assessing industry benchmarks to gauge data strategy success and guide cross-team evaluation on domain coverage and realism
• Scale expertise by recruiting SMEs, acting as domain authority to enforce vendor quality, and converting expert contributions into training and evaluation data

Key requirements

• Master’s degree in Finance, Economics, Business Administration, a related quantitative field, or equivalent practical experience
• Experience measuring the performance of Large Language Models (LLMs) or generative AI tools and optimizing them for financial use cases

• Excellent cross-functional communication
• Collaboration with technical partners
• Leadership and stakeholder management
• Proficiency in programming for evaluating machine learning models
• Experience applying Large Language Models to complex financial workflows
• Strong technical and research capabilities in ML model evaluation

…