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Lightly AG is an ETH and HSG spin-off pioneering in machine learning and computer vision. Backed by Y Combinator and top-tier investors, our technology is used by global leaders in autonomous driving, medical imaging, and visual inspection. With a small but sharp team in Zurich, we’re looking for analytical and driven Finance Professionals to help us translate complex finance concepts into AI-readable formats. This role suits someone with a background in finance, economics, or engineering with experience in any of the following: • Corporate Finance • Private Equity / Venture Capital • M&A / Investment Banking • Asset Management • Accounting Estimated project scope of approximately 15 hours/week. Project expected to begin early July. Tasks We are launching a project focused on evaluating AI-generated financial analysis and market event reasoning. You'll review AI outputs covering stock price movements, earnings events, commodity dynamics, and cross-market relationships — and assess whether the AI's logic actually holds up. You'll be a good fit if you have experience in equity research, financial analysis, or quantitative finance, and are comfortable with: • OHLCV (Open, High, Low, Close, Volume) stock data and price-volume relationships • Earnings-driven price movements and market event analysis • Commodity markets — energy (crude, natural gas), metals (gold, silver, copper), agriculture (corn, soybeans, wheat, coffee) • Cross-channel analysis — understanding how price channels and volume interact • Financial news verification — checking whether cited market events actually happened Requirements You’re a strong candidate if you: • Are fluent in English • Have strong analytical and quantitative skills and are confident working with financial models and valuation frameworks • Communicate clearly and precisely Benefits • Work directly with a YC-backed team on cutting-edge AI evaluation projects • Competitive compensation tailored to experience and scope of work Send us your CV and a short note about why this role excites you. If you’ve handled similar tasks before, we’d love to hear specific examples. We look forward to hearing from you!