Wind Manufacturing Finance Intern: Data-Driven Ops & CAPEX

gevernova; Issy-les-Moulineaux; On-site; EUR 12,000 - 19,000; Part time

Job summary

gevernova in Île-de-France (Issy-les-Moulineaux) seeks a Wind Manufacturing Finance Intern to support financial analysis across manufacturing operations, CAPEX investments, and inventory management, working closely with the Finance Director to evaluate supply chain performance.

The ideal candidate is analytical, detail-oriented, proficient in Excel and data analysis, comfortable with large data sets and financial models, and eager to identify cost optimization opportunities.

Qualifications

• Analytical and detail-oriented with ability to work with large datasets and financial models.
• Proactive with strong Excel/data analysis skills.
• Interest in finance, operations and supply chain performance.

Responsibilities

• Support financial analysis for manufacturing facilities within the Wind segment.
• Support financial analysis and trend analysis on CAPEX investments across the supply chain.
• Analyze inventory trends, working capital drivers, and opportunities for operational improvement.
• Prepare management reports, dashboards, and ad hoc analyses to support decision-making.
• Help identify risks, cost optimization opportunities, and performance improvement actions.
• Collaborate with finance and cross-functional business partners to gather data and develop insights.

Skills

Excel

Data analysis

Financial modeling

Attention to detail

Analytical thinking

Proactive mindset

Supply chain performance

Education

Pursuing degree in Finance/Accounting/Operations

Tools

LLMs

Job description

gevernova in Île-de-France (Issy-les-Moulineaux) seeks a Wind Manufacturing Finance Intern to support financial analysis across manufacturing operations, CAPEX investments, and inventory management, working closely with the Finance Director to evaluate supply chain performance.

The ideal candidate is analytical, detail-oriented, proficient in Excel and data analysis, comfortable with large data sets and financial models, and eager to identify cost optimization opportunities.