Many large companies make billions each year by monetizing Americans’ personal data. At Neon, we’re finally cutting consumers in on the deal. Neon allows our users to make hundreds (or even thousands) of dollars per year by securely selling their anonymized data.
We recently raised over $25 million from investors including Lightspeed, Upper90, and Upfront Ventures.
About the Role
We’re building something big at the intersection of media, consumer data, and AI. We’re seeking a Senior Data Scientist to define and drive the analytical and experimental work that connects our data systems to real business and customer outcomes.
You’ll be a strategic partner across product and engineering, helping shape decisions around experimentation, tooling, and insights that matter most to our users.
Own end-to-end experimentation and analytical workflows that help the business learn fast and make confident decisions rooted in data.
Work closely with product, data engineering, and business stakeholders to start with customer and business goals, and work backwards to design the right experiments, features, metrics, and models.
Focus initially on optimizing our data pipeline for media data (audio and text) — helping improve throughput, quality, and utility of data as it flows through our systems.
Contribute to the evolution of our data infrastructure to support more advanced capabilities — including eventual creation of novel datasets and internal modeling workflows (e.g., for voice or multimodal data).
Design, analyze, and interpret experiments across tools/services/technologies to identify what works best — producing actionable insights that influence product direction, operations, and future research.
Translate complex analytical outcomes into clear business insights and product recommendations, occasionally contributing to broader thought leadership and research narratives.
Strong analytical background (e.g., statistics, experimentation, causal inference) with several years of real-world experience in data science or research-oriented roles.
Comfort operating independently and pragmatically in a startup environment, balancing speed and rigor.
Excellent communicator who can bridge technical and business audiences — asking the right questions, framing hypotheses, and presenting findings effectively.
Demonstrated ability to guide experimentation from design through interpretation, and connect results back to product and business levers.
Experience with media-centric data (audio, video, text) and related tooling or models.
Familiarity with machine learning workflows, model evaluation, and production experimentation frameworks.
Additional experience with OOP languages, particularly JavaScript
Bonus points if you’ve worked closely with voice AI, speech, or related media AI labs or contributed to their research efforts.
Competitive compensation with equity upside
Opportunity to shape direction of analytics and modeling at an early stage
A collaborative team environment and a fun, can-do attitude! :)
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