Energy & Renewables Finance - AI trainer

Job Title: Energy&Renewables Finance-AItrainer

Job Type: Part-time

Location: Remote

Joinourcustomer’steamasan

Energy&Renewables Finance-AItrainerandplayapivotalroleinshapingthenextgenerationof

AIsystemsforfinance.

Thispart-time,remotepositionoffersauniqueopportunitytoleverageyourindustryexpertiseinenergyandrenewablesfinance,working hands-onwithbroad,real-worlddatasetsandcollaboratingon

AImodelsthatdrivemeaningfulimpact.

• Analyze and interpret complex, messy spreadsheets and real-world financial data from the energy and renewables sector.
• Seed and structure ambiguous or incomplete financial data and artifacts for AI model training.
• Collaborate with cross-functional teams to develop effective data annotation and model improvement workflows.
• Assess and validate finance-adjacent data inputs, identifying opportunities for normalization and model extension.
• Utilize written and verbal communication skills to document processes, surface challenges, and articulate findings clearly.
• Participate in iterative data seeding and structuring processes, adapting to evolving project needs and flows.
• Contribute to refining AI models by providing expert insights into industry-specific finance scenarios and data patterns.

• Proven background in energy, renewables, or related finance fields.
• Experience working with unstructured, incomplete, or “in-the-wild” financial datasets.
• Exceptional written and verbal communication skills, with a focus on clarity and collaboration.
• Strong attention to detail and ability to manage ambiguity in data and workflows.
• Familiarity with spreadsheet tools and finance modeling techniques.
• Comfortable with remote collaboration across US, Canada, UK, and EU regions.
• Demonstrated adaptability to dynamic, evolving project requirements and rapid feedback cycles.

• Prior experience in AI training, data annotation, or machine learning environments.
• Exposure to energy or renewables investment analysis or project finance.
• Understanding of data normalization and model evaluation in finance contexts.