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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.
Job Responsibility:
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 the actionable insights that drive our strategy
Translate complex data into clear, compelling narratives that drive alignment and decision-making across the organization
Requirements:
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
hands-on builder with experience creating and maintaining a modern data stack (e.g., ETL, data warehousing, visualization tools)
proactive, first-principles thinker who is driven to define and implement core metrics and experimentation frameworks in an ambiguous environment
deep understanding of product analytics, growth metrics, and A/B testing methodologies
exceptional communicator and a natural collaborator, with a proven ability to build strong relationships and influence decision-making across all levels of an organization
Nice to have:
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