Senior Data Scientist, Business Analytics

About Us Venice is the world’s leading consumer AI company built on principles of privacy, free speech, and user sovereignty. We’re building the Port City of AI, in which millions of individuals, third party apps, and AI agents gather, interact, and access sophisticated AI resources on a private and permissive foundation. Our mission is to make artificial intelligence approachable and useful in everyday work—bridging the gap between cutting-edge research and practical, real-world impact. We’re a fast-moving startup where every team member is expected to make a clear impact. Our culture is rooted in curiosity, ownership, ethical principle, philosophy, and collaboration—whether we’re designing better AI workflows, supporting our growing community, or shaping the future of human-AI interaction. Joining Venice AI means joining a team of unorthodox builders who believe in moving quickly, delivering a beautiful mass-market and highly useful consumer product that doesn’t spy on people or censor their ideas and questions., and maintaining an edge in the rapidly evolving world of agentic machine intelligence. If you’re energized by big ideas, entrepreneurial spirit, individual empowerment, and the opportunity to help shape a fast-growing company in the world’s hottest industry from the ground up, please reach out.you’ll feel right at home here. Why We’re Hiring Venice is growing fast! Every day we are shipping new products, expanding into new modalities, and making decisions that shape the future of the platform. We know that to make the right decisions, they need to be grounded in data. Venice is a privacy-first company, which means we deliberately collect less user data than most companies in our space. We don’t track what we don’t need and we don’t store what we shouldn’t. This is a core part of who we are, and it’s not negotiable. This creates a real analytical challenge: How do you inform business insights when you have limited user data? How do you make confident product decisions when you have less data than your competitors? How do you separate signal from noise without the crutch of exhaustive user tracking? To help us answer these questions, we’re hiring a Senior Data Scientist who operates as a tactical analytics leader to be the authoritative source on data at Venice. You will own where data is sourced from, where it is stored, how it is accessed and how it is queried. You will build the systems and provide the answers the business needs, with oversight, auditability, and clean code. You’ll be the person who not only bridges the gap between our privacy principles and our need for rigorous, data-driven product decisions, but also who proactively surfaces the strategic questions leadership hasn’t asked yet - anticipating what matters to the business. You will know the data like the back of your hand. We don’t want someone fighting the privacy model; we want someone to successfully work within it. This role will report to the VP of Business Operations and will work closely with product managers, engineering, finance, marketing and the leadership team. Your job is to ensure that every major business and product decision is backed by analysis that’s both rigorous and honest about its limitations. What You’ll Do Own the data, end to end. Decide where data lives, how it flows, and how it's queried. Build the infrastructure, tooling, and dashboards that make you the expert on company data, from raw sourcing through to the insights that shape business and product decisions. Everyone should be able to point to your work as the ground truth. Consolidate data access. Ensure the business accesses data consistently - including financial statements, product metrics, and growth analysis. No isolated islands, no duplicate systems. Build a shared data lake with specialized views on top. Support experiment tracking. While experimentation strategy lives with Product, you will help track experiments, building the systems so Product can monitor tests without managing spreadsheets. Ask and answer strategic questions about the business and our products. Be honest about uncertainty. You proactively identify what questions will be asked and bring answers to the table with analysis. You won’t have the luxury of exhaustive telemetry. You’ll need to be creative: derive insights from the data we do have, use statistical methods that work with small samples, and be transparent about confidence levels. When the data isn’t enough to be certain, say so. Recommend the decision anyway, with appropriate caveats. False certainty is worse than acknowledged uncertainty. Build the analytical foundation. We have an internal data warehouse and product analytics tooling. You’ll assess what’s there, identify gaps, and build what’s missing. This might include dashboards, self-serve analysis tools for product managers, data models, and reporting pipelines. The goal: make analytics accessible to decision-makers without requiring them to come to you for every question. Partner across the org. You bring insights to internal stakeholders to guide and reshape roadmaps. Work with engineering to instrument products thoughtfully: collecting what’s needed for decisions without collecting what isn’t. Work with finance on business metrics. Work with marketing on growth attribution. Work with the executive team on company-level metrics and strategic questions. Protect the privacy line. Be the analytical voice that says “we don’t need to collect this” when new tracking is proposed. Help the team understand the tradeoff between data granularity and user trust. Find analytical methods that don’t require invasive tracking. This is not about blocking progress; it’s about finding the path that keeps both the product and the principles intact. Separate signal from noise in a fast-moving product. Venice ships constantly. New models, new features, new modalities, new revenue streams. You’ll need to build metrics that are robust to this pace of change, and help the team distinguish real trends from noise when the product is evolving week over week. *We retain the right to change or assign other duties to this position. Who You Are You're a product-minded data leader with engineering depth. You have 7+ years of demonstrated experience, but you’re not just a technical executor, you think like a product manager and business owner first. You understand that the goal is better decisions, not more dashboards. You surface the questions that matter and can translate a business question into an analysis and put forth a recommendation. You think about the API funnel, where users come from, and conversion. You've worked in environments where data is messy, incomplete, or deliberately constrained, and you find creative ways through it: quasi-experiments, proxy metrics, qualitative triangulation, and decision frameworks that work with what you have. You can work in the DB and partner with Engineering to influence robust data systems. You write production-quality code, you're fluent in SQL, and you can build data pipelines, models, and tooling that become infrastructure. You understand data warehousing concepts and have worked with modern analytics stacks. Venice's stack includes Rust, TypeScript, Go, and Python; familiarity with more than one is a plus. You have experience with PostHog for product analytics and Postgres for data storage and querying, and you understand PostHog's potential as a central platform across error tracking, support, and conversation data. You communicate clearly, especially about uncertainty. You can present to the executive team without hiding behind jargon. You're honest about what the data shows and what it doesn't. You don't overclaim. You can say "I'm 70% confident in this direction" and explain what would change your mind. You help decision-makers act under uncertainty rather than wait for certainty that won't come. You respect the privacy mission. You understand why Venice collects less data than competitors, and you agree with it. You're not looking for ways to work around the constraint. You're looking for ways to make great decisions within it. You've thought about the ethics of data collection and have opinions about what companies should and shouldn't track. You move fast and iterate. You prefer a rough analysis this week that informs a decision over a perfect model next month that's too late. You iterate on methods and tooling in production. You identify what’s needed, advocate for it, and see it through. You're also excited about using AI agents as part of your workflow: leveraging LLMs to accelerate analysis, automate repetitive data work, and surface insights faster. You see agents as a tool that makes you more productive, not a threat to the analytical craft.