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Posted on 2026/01/01

Consumer & Retail Finance - AI trainer

micro1

via Jobs.micro1.Ai

Part-time

Full Description

Job Title: Consumer & Retail Finance - AI trainer

Job Type: Part-time

Location: Remote

Job Summary:

Join our customer’s team as a Consumer & Retail Finance - AI trainer and help shape the next generation of AI models in the finance sector.

In this dynamic, remote role, you’ll leverage your industry experience and communication skills to seed and refine real-world financial data, enabling breakthrough AI capabilities in consumer and retail finance.

Key Responsibilities:

  • Curate and seed messy, real-world consumer and retail finance data sets for AI training purposes

  • Engage with partial models, ambiguous inputs, and complex spreadsheets to support model development

  • Annotate and structure data artifacts, balancing initial seeding with iterative organization

  • Provide valuable feedback to the data science team to improve model performance and accuracy

  • Work collaboratively with finance-adjacent professionals across the US, Canada, UK, and EU

  • Document observations and best practices in clear, well-organized written formats

  • Participate in regular project meetings, sharing insights and communicating progress

Required Skills and Qualifications:

  • Demonstrated background in consumer or retail finance, with exposure to financial operations or data

  • Exceptional written and verbal communication skills; clarity and thoroughness are essential

  • Experience working with unstructured or messy data such as spreadsheets and finance artifacts

  • Analytical mindset with the ability to understand and normalize ambiguous information

  • Proficiency in remote collaboration and self-directed project management

  • Adaptability to shifting project flows, including iterative data seeding and structuring

  • Detail-oriented approach to contributing to broad, evolving AI training initiatives

Preferred Qualifications:

  • Prior experience with AI, machine learning, or data training projects

  • Familiarity with finance data models or annotation tools

  • Exposure to cross-functional or international teams in a technology-driven environment

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