Product Data Analyst

Celigo

9h•Remote

About The Position

At Celigo, we believe integration should empower — not exhaust — innovation. As a modern Integration and Automation Platform (iPaaS), we’re on a mission to simplify how companies integrate, automate, and optimize processes. Powered by game-changing technology like runtime AI and prebuilt, mission-critical integrations, Celigo is redefining how businesses connect their world. As a Product Data Analyst you will play a critical role in Celigo’s success and help execute quantitative research tasks throughout the product development lifecycle to ensure that we’re solving the right problems and providing the right solutions for our target audiences and users. The Product Data Analyst works strategically, proactively, and collaboratively to inform and influence product roadmaps and business goals. We are seeking a Product Data Analyst to partner closely with UX Research, Product Management, Design, Content, Engineering, and Customer-facing teams to uncover actionable insights from behavioral and product usage data. This role sits within the UX Research team in the Product organization and will partner closely with product managers and designers to uncover actionable insights from behavioral and product usage data. This is not a reporting-only role. It is a strategic position focused on uncovering, identifying, and transforming complex data into clear recommendations that drive measurable improvements in user experience, adoption, retention, and business impact.

Requirements

Strong attention to detail and problem-solving skills, along with exceptional written and verbal communication skills.
Ability to multitask and operate as a consultant across multiple product areas.
Ability to analyze and synthesize data, and guide product managers, designers, and engineers on how to act on the findings.
Aptitude for learning complex technological concepts.
Actively seeks and offers candid, constructive feedback with curiosity, humility, and openness.
4–6+ years of experience in Product Analytics or a similar role supporting B2B SaaS or enterprise software products.
Strong SQL skills and experience querying large datasets from multiple applications in a data warehouse (e.g., Snowflake).
Experience working with product analytics tools (e.g., Pendo, Google Analytics) and BI tools (e.g., Sigma).
Experience in defining and measuring KPIs such as activation, engagement, retention, churn, and feature adoption.
Work samples (case studies, portfolio, website, or similar) demonstrating the depth and breadth of your abilities, and their impact on the business.
Experience working in B2B SaaS, enterprise, or technically complex platforms.
Proven experience working with multi-disciplinary teams (Design, Engineering, Business, R&D, and others) to ideate, iterate, launch, and refine new product designs.
Degree in Statistics, Data Science, Economics, Computer Science, or related quantitative field (or equivalent experience).

Nice To Haves

Experience with statistical tools (e.g., R, Python). Experience with methods such as cluster analysis, multivariate regressions, and two-proportion Z-tests is a plus.

Responsibilities

Partner with members of the Design, Content, and Product Management teams to uncover what they need to learn from quantitative data sources (and why) and then identify, pull, and analyze the necessary data to provide them with actionable insights rather than tables of raw data.
Collaborate closely with designers to define, track, and report on metrics that demonstrate the business and user impact of their work as well as craft measurable hypotheses for new and existing features.
Be curious, proactively analyze data, and surface insights that influence product strategy, roadmap decisions, and customer experience improvements.
Help train peers to effectively utilize user research findings and usage metrics to guide and improve design decisions.
Support research operations tasks such as pulling recruitment lists and answering ad-hoc data questions.
Build and maintain dashboards and self-serve reporting frameworks that empower cross-functional teams.
Translate ambiguous business questions into structured analyses and clear recommendations.
Identify leading indicators of engagement, activation, retention, and expansion.
Collaborate with Product Operations, Engineering, and Data teams to ensure clean, reliable event tracking and instrumentation.
Influence stakeholders across functions to gain support for research-based, user-centric solutions.