Product Operations Analyst - Product Analytics

We’re hiring a Product Operations Analyst to strengthen how R&D decisions are made at DoiT and to help drive our AI transformation across the organization.

This role is built for someone who cares deeply about business results, not just the data itself. You care about the customers we serve and use AI tools, data, and voice of the customer systems as tools to improve how we discover, define, build, mature, and iterate our products.

You’ll operate at the intersection of product, data, AI, and customer insight helping build and maintain the measurement and analytics foundations that ensure our product investments are grounded in reliable signals and real customer needs.

Reporting to the Head of Product Operations and part of the Product and R&D organization, this is a high-impact individual contributor role suited for someone with strong data, analytics, and AI experience who enjoys building scalable processes and working cross-functionally.

As DoiT’s product portfolio grows, clear measurement and structured customer insight become increasingly important. This role helps ensure that product decisions are informed, measurable, and aligned with business outcomes, enabling the team to build with greater confidence and focus.

Responsibilities

1) Product Measurement & Instrumentation

Support and evolve the framework and systems that turn product behavior into trusted, actionable signals:

• Partner with Engineering to define and maintain event taxonomy, tracking standards, and instrumentation quality
• Build and maintain scalable, self-service dashboards for product teams
• Help establish and document clear metric definitions as a shared source of truth.
• Contribute to improving how and what we measure as the product evolves.
• Leverage AI to repeatedly unlock insights and recommendations from these signals

Outcome: Product teams have reliable data to evaluate performance and make informed decisions.

2) Analytics & Data Foundations

Strengthen the product analytics ecosystem and data models that power decision-making.

• Work within our product analytics stack (e.g., Mixpanel, Segment, Looker) to ensure accurate and accessible reporting.
• Build and maintain dbt models for core product entities and behaviors.
• Contribute to a clean, usable metric layer for business stakeholders.
• Help structure and analyze Voice of the Customer inputs (e.g., support, churn, NPS, sales feedback, customer interviews)
• Support data quality through testing, monitoring, documentation, and automation
• Deploy the best AI tooling available to make our data a differentiator

Outcome: Product data is systematically consistent, accessible, and trusted.

3) Insight Generation & Reporting

Translate product usage and customer signals into clear, actionable insights.

• Deliver recurring product analytics reporting (adoption, engagement, retention)
• Contribute to analytics readouts to business stakeholders and executives with clear findings and recommendations
• Perform analyses that connect product behavior to revenue and retention outcomes
• Support automated reporting and AI-assisted workflows while maintaining metric integrity
• Strive to make insights and reporting automated and self-service, heavily assisted through best practices with emerging AI techniques

Outcome: Product and business stakeholders regularly use analytics and customer insights to inform roadmap and investment decisions.

Qualifications

• 5+ years of experience in product analytics or related roles. Experience working closely with digital product teams and influencing decisions through data.

AI-First mentality. Must have a practical understanding of how AI is reshaping analytics workflows. The ideal candidate will have experience using AI to accelerate insight generation, documentation, and distribution while understanding how to build guardrails, trust, and safe operationalization of AI.

• Systems thinker & operator's mindset. Track record of building systems that scale across many groups.
• A “Builder” mindset. We have bold ambition, and we move fast. Whether we’re missing processes, systems, tools, data, or buy-in, your instinct must be to create, solve, and build paths that may not exist today.
• Comfort operating in ambiguity. Ability to prioritize, structure problems, and execute independently while collaborating across teams.

Clear communicator. Experience presenting analysis to product managers and business stakeholders, translating complex findings into actionable recommendations. Strong analytical foundation. Advanced SQL required. Experience with event-based analytics and familiarity with tools such as Mixpanel (or similar), Looker (or similar BI tools), Segment (or similar), and dbt. Domain familiarity (preferred). Exposure to public cloud environments (AWS, GCP, Azure), FinOps/cloud cost management, and enterprise SaaS company concepts is preferred.

How success will be measured

• Product teams rely on analytics to evaluate feature performance and guide roadmap decisions
• Core product metrics are clearly defined, trusted, and consistently used
• Product insights contribute to improvements in adoption, engagement, and retention
• Voice of the Customer signals are organized and incorporated into feedback loops
• Data is readily accessible, well-documented, and clear, enabling efficient decision-making
• Analytics and insights are available quickly and require less manual effort
• AI is being used across our product operating model to incorporate signals into every decision across Product, Design, and Engineering
• AI-driven insights are systematically integrated to inform and optimize critical decision-making throughout every phase of our product lifecycle, from initial concept to post-launch iteration.