Energy & Renewables Finance Expert

Job Title: Energy & Renewables Finance Expert

Job Type: Part-time

Location: Remote

Job Summary:

Join our customer’s team as an Energy & Renewables Finance Expert and play a pivotal role in shaping the next generation of AI systems for finance. This part-time, remote position offers a unique opportunity to leverage your industry expertise in energy and renewables finance, working hands-on with broad, real-world datasets and collaborating on AI models that drive meaningful impact.

Key Responsibilities:

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

Required Skills and Qualifications:

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

Preferred Qualifications:

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