Data Scientist

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This is a foundational, zero-to-one opportunity to build Luma's entire data science discipline from the ground up. As our first Data Scientist, you will be the architect of our data-driven culture, defining the north-star metrics that guide our strategy and building the source-of-truth systems that empower the entire company. This is not a role for running queries; you will be a strategic partner across product, growth, and research, uncovering the critical insights that will shape the future of our creative AI platform.

• Architect and build our data science and data engineering infrastructure and source-of-truth dashboards from scratch, creating a self-serve platform that empowers the entire company.
• Define and champion the north-star metrics that guide our product, growth, and research initiatives, establishing a data-driven culture from the ground up.
• Design and analyze the key experiments that measure the impact of product changes, growth initiatives, and new model deployments on our users.
• Partner directly with leadership and embed across product, growth, and research teams to uncover and deliver actionable insights that drive our strategy.
• Translate complex data into clear, compelling narratives that drive alignment and decision-making across the organization.

• You have 7+ years of experience in data science, ideally as a founding or lead data scientist or data engineer at a high-growth product or technology company.
• You are a hands‑on builder with experience creating and maintaining a modern data stack (e.g., ETL, data warehousing, visualization tools).
• You are a proactive, first‑principles thinker who is driven to define and implement core metrics and experimentation frameworks in an ambiguous environment.
• You have a deep understanding of product analytics, growth metrics, and A/B testing methodologies.
• You are an exceptional communicator and a natural collaborator, with a proven ability to build strong relationships and influence decision‑making across all levels of an organization.

• Experience working with data from generative AI, creative tools, or media‑rich products.
• Familiarity with the data infrastructure required to support large‑scale ML systems.
• A strong portfolio of public‑facing analyses, data visualizations, or open‑source contributions.
• Experience setting up a data science function from zero at a previous startup.