Job Description

Why This Role Exists

At Smartcat, we believe analytics should not simply explain what happened. It should actively shape what happens next.

As an AI-First Product Analyst, you will partner primarily with Product leadership while also supporting strategic initiatives from the Office of the CEO. Your defining mandate is to work AI-first: rather than building dashboards and pulling reports by hand, you'll teach and enable Scout (our company AI agent) and other AI teammates (personal agents) to handle analytics requests autonomously — so that when a stakeholder needs a dashboard or an answer to a data related question, they can get it from Scout directly, and you step in only on the problems that genuinely need a human.

This role is fundamentally different from a traditional BI analyst. We are not looking for a task-doer who services a queue of dashboard requests. We are looking for an analyst-thinker who actively helps stakeholders reason about their data instead of just delivering it.

You will spend your time on two things: (1) enabling Scout — identifying what it takes to answer a recurring question, building the data and logic behind it, and teaching the system to do it reliably going forward; and (2) tackling the harder analytical problems — investigating product hypotheses, uncovering hidden growth opportunities, challenging assumptions with data, and proposing better ways to analyze the business. As the AI layer takes on the repetitive work, your leverage compounds.

We are looking for someone who combines analytical rigor, business curiosity, AI fluency, and startup execution speed.

Mission

Enable Smartcat to make better product and business decisions through AI-powered analytics, scalable data products, and actionable insights that drive customer growth, adoption, retention, and expansion.

Requirements

Experience

• 5+ years of experience in Product Analytics, Product Intelligence, Growth Analytics, or related analytical roles.
• Proven experience supporting Product organizations in SaaS or technology companies.
• Demonstrated track record of driving business outcomes through analytics and insights.
• Experience working in fast-paced, high-growth startup environments.

Technical Skills

• Advanced SQL proficiency, including:
• Complex joins
• Window functions
• Query optimization
• Common Table Expressions (CTEs)
• Large-scale data analysis
• Experience with Business Intelligence platforms such as:
• Looker
• Omni
• Grafana
• Similar modern BI tools
• Ability to build and maintain scalable dashboards and reporting systems.
• Python experience for data analysis is strongly preferred.

AI Fluency (Required)

This is an AI-first role.

Candidates should demonstrate an Adoptive or Transformative level of AI fluency and be able to show examples of:

• Using AI to redesign analytical workflows.
• Automating repetitive reporting processes.
• Building AI-assisted research and analysis systems.
• Leveraging multiple AI tools to improve speed and quality of decision-making.
• Applying AI beyond simple prompting to create measurable business impact.

Business & Communication Skills

• Exceptional analytical and problem-solving abilities.
• Ability to sift through large amounts of information and identify the most important signals.
• Strong business judgment and curiosity.
• Excellent communication skills with the ability to tailor insights for technical and non-technical audiences.
• Ability to influence stakeholders through data-driven recommendations.
• Comfortable working independently with significant ownership.

Additional Qualifications

• Experience collaborating across Product, Revenue, Customer Success, and Engineering organizations.
• Experience working with distributed global teams across multiple time zones.
• Basic understanding of Machine Learning concepts is a plus.
• Receptive to feedback and committed to continuous improvement.

Who Thrives Here

• Highly analytical and deeply curious.
• Obsessed with understanding the real problem before proposing solutions.
• Comfortable challenging assumptions with data.
• Acts quickly and embraces ambiguity.
• Uses AI as a force multiplier.
• Thinks like an owner.
• Loves turning complexity into clarity.
• Balances strategic thinking with hands-on execution.