Remote Personal Financial Advisor

Turing•San Francisco, CA

2d•Remote

About The Position

Turing is seeking experienced financial advisors and planners with a background in personal finance, investment management, retirement planning, and tax optimization. The role involves using financial advisory expertise and communication skills to support projects that fine-tune and evaluate large language models (LLMs). No prior AI experience is required. The projects provide an opportunity to learn how AI can improve client experience, advisory workflows, and the quality of financial planning insights. Day-to-day work includes designing and solving real-world financial advisory scenarios and case studies to assess AI reasoning; writing clear, structured financial solutions reflecting real-world advisory decisions; collaborating with AI researchers to improve model understanding of risk profiling, asset allocation, and investment strategy; and refining evaluation benchmarks grounded in financial planning principles, regulatory standards, and industry best practices. This is a contractor/freelancer engagement. Projects last approximately one month, with the possibility of extension, and may potentially be full-time. Compensation varies by project. The work is fully remote. Contributors must not provide confidential or proprietary information, trade secrets, internal organizational data, specific client information, or information that would violate confidentiality obligations.

Requirements

At least 4 years of experience as a Personal Financial Advisor, Wealth Manager, Financial Consultant, or in a similar role.
Bachelor’s or Master’s degree in Finance, Economics, Accounting, Business Administration, or a related field.
Strong English communication and analytical skills.
Ability to explain complex financial concepts in simple, client-focused language, using data and visuals where needed.

Nice To Haves

Professional certification such as CFP®, CFA®, or CPA®; preferred but not mandatory.

Responsibilities

Design and solve real-world financial advisory scenarios and case studies to assess AI reasoning.
Write clear, structured, high-quality financial solutions that reflect real-world advisory decisions.
Collaborate with AI researchers to improve model understanding of risk profiling, asset allocation, and investment strategy.
Help define and refine evaluation benchmarks based on financial planning principles, regulatory standards, and industry best practices.