Product Data Analyst

About us

We've been profitable since day one. Never raised a dollar. Quietly built one of the most efficient programmatic acquisition engines on the planet, processing billions of ad decisions a day, generating TBs of live behavioral data, and turning it into margin most SaaS companies would kill for.

Now, we're setting out to increase the company's visibility and positioning in the market. The AI wave cracked open a window to reposition the business, launch our consumer AI products (amongst them Ace AI browser), and access capital markets for the first time.

About Ace

We're building a new B2C AI browser that will soon be in the hands of millions. Radically simple, delightfully fast, and enhanced by powerful AI features. Our mission is to simplify and improve daily online activities.

We've shipped a beta, and the user base keeps growing daily. The surface area ahead is wide: AI features, system-level interactions, and cross-platform experiences on desktop and mobile.

Learn more at ace.ai.

We're looking for an ambitious Product Data Analyst to own the numbers behind Ace and play a central role in shaping product decisions.

This is not a reporting role. You’ll work closely with Product, Engineering, Growth, and company leadership to understand how people use Ace, identify opportunities, design and evaluate experiments, and help decide what we should build or improve next.

You’ll own the analytical process end to end: identifying the right questions, defining metrics, designing experiments, working directly with product data, interpreting results, and translating findings into clear product decisions.

We move fast, experiment constantly, and expect analysts to be hands-on, curious, technically strong, and comfortable challenging assumptions.

What You'll Do

• Own the consumer funnel end to end. Analyze acquisition, install, onboarding, activation, engagement, retention, and monetization across desktop and mobile. Identify where users drop, understand why, quantify the opportunity, and turn insights into concrete product opportunities.
• Run the experimentation engine. Own experiments end to end - identify what’s worth testing, define the right metrics and methodology, analyze the results, and translate learnings into clear product decisions.
• Go deep into the data. Work directly with large-scale behavioral data to investigate questions, uncover patterns, diagnose problems, and find opportunities that aren’t obvious from a dashboard.
• Shape how we measure the product. Define the metrics that matter, make sure we’re measuring new features correctly, and create a trusted analytical foundation for understanding product performance.
• Be a strategic product partner. Work closely with Product and leadership to frame important questions, challenge assumptions, and bring a strong data-driven perspective to product strategy and prioritization.
• Use AI to work differently. Use modern AI tools as part of your daily workflow to explore faster, investigate deeper, automate repetitive work, and build lightweight solutions when needed.
• Make the organization faster with data. Build frameworks and self-service capabilities that help teams answer common questions independently, so your time stays focused on the highest-impact problems.

• 3+ years as a Product Analyst or Data Analyst in a fast-paced product environment. Consumer product experience is a strong plus.
• Excellent SQL and analytical skills. You’re comfortable working directly with large, complex datasets and can independently get from a product question to a trustworthy answer.
• Strong experimentation skills. You understand how to design, evaluate, and interpret A/B tests, including the statistical principles and practical pitfalls behind them.
• Strong product thinking. You don’t stop at what happened - you want to understand why it happened, what it means for the user and the business, and what we should do next.
• Technical curiosity. You’re comfortable understanding how products work under the hood and collaborating with engineers on data, instrumentation, experiments, and technical product questions.
• AI-native mindset. AI is already part of how you work. You actively use modern AI tools to increase your speed, depth, and independence.
• High ownership. You don’t wait for perfectly defined requests. You identify important questions, investigate them independently, and drive them toward decisions.
• Strong communication. You can turn complex analysis into simple, clear conclusions that people can understand and act on.

Advantages

• Experience working on consumer products at a meaningful scale.
• Experience with growth, retention, engagement, or subscription products.
• Experience analyzing products across both desktop and mobile.
• Python or other programming experience for analysis and automation.
• Experience building analytical frameworks, data models, or internal analytical tools.