Senior Product Data Analyst at AirHelp

Gdańsk, Pomeranian Voivodeship, Poland -

Full Time

Start Date

Immediate

Expiry Date

14 Sep, 26

Salary

70000.0

Posted On

16 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Behavioral Analytics, Google Analytics, A/B Testing, Experimentation, Data Curation, Product Strategy, Funnel Analysis, Cohort Analysis, Event Tracking, AI-Native Development, Data Modeling

Industry

IT Services and IT Consulting

Description

AirHelp is a global tech company specializing in air travel protection. So far, we have helped millions of travellers claim compensation for disrupted flights. As we scale our digital products, data-driven decision-making is becoming a core competitive advantage. We're investing in product analytics to ensure every product squad operates with sharp insight, rigorous experimentation, and AI-powered self-service. We're looking for a Senior Product Analyst to embed within our product-engineering tribes and drive measurable impact across three critical areas: claims adoption on mobile, conversion funnel optimisation, and the growth and retention of our AH+ Subscription product. You'll play a strategic role in shaping product direction with data, while also owning the data curation pipeline that powers our AI-driven data products. This role sits at the intersection of product strategy, experimentation, and AI-native ways of working. You won't just answer questions with data. Your task will be to challenge assumptions, define what to measure, and help product managers move faster through self-service analytics powered by AI. This is a hybrid job opportunity in Barcelona, Warsaw or Gdańsk. Salary: 55,000 - 70,000 EUR gross/annually on Employment contract. What you'll be working on: Embed within product engineering squads to provide strategic analytical support, partnering closely with Product Managers and engineers to define hypotheses, measure feature performance, and inform product direction through data-driven insights. Conduct analyses to better understand traveller needs and behaviours across every stage of their journey. Improve AirHelp mobile app monetisation by identifying friction points in the claims submission journey and AirHelp Plus sales experience. Lead the data curation process end-to-end by ensuring we capture, clean, and expose the right behavioural and transactional data to power internal downstream AI products. Enable product self-service by collaborating with data engineers to build AI-powered analytics workflows that allow Product Managers to answer their own questions without analyst bottlenecks. Partner with engineers on event tracking, instrumentation, and data ingestion - making sure measurement is built into features from day one, not bolted on after launch. Develop deep funnel and cohort analysis across the customer lifecycle, surfacing insights that inform both day-to-day optimisation and longer-term product strategy. Contribute to the analytics craft at AirHelp through systems thinking, knowledge sharing, and raising the bar for how data is used across product teams. What you’ll deliver in your first 12 months: Drive a measurable increase in AirHelp mobile app monetization, growing claim submission share to at least 15% with experimentation as the primary lever. Build understanding of how engagement with the app while traveling contributes to additional user actions. Improve AirHelp Plus conversion and retention to enable revenue growth in B2C (aiming at 30% YoY growth), with a clear analytical narrative behind every gain. Stand up a robust experimentation practice across at least three product squads - with shared standards for hypothesis design, sample sizing, and result interpretation. Deliver a clean, well-documented event taxonomy and data model that powers both product analytics and our AI-driven product. Enable Product Managers to self-serve the majority of their analytical questions through AI-powered workflows, freeing analyst time for higher-leverage strategic work. Establish yourself as the analytical partner of choice within your product tribes - trusted to challenge direction, frame problems, and shape roadmaps with data. What sets you apart: You have proven experience in data analytics within product engineering environments, including close collaboration with Product Managers to define feature measurement frameworks. You are proficient in SQL, including the ability to clean, extract, and manipulate data. You're fluent in behavioural analytics platforms, and you also know your way around Google Analytics. You're experienced in designing and delivering meaningful A/B tests using experimentation platforms such as GrowthBook or Optimizely, with a strong understanding of sample sizing, novelty effects, and segmentation. You're previously worked in AI-native development environments, with extensive day-to-day use of agentic coding tools such as Claude Code and Codex as a core part of the engineering workflow. You have the ability to apply a product-oriented mindset to analytics and challenge product strategy constructively, using data-driven perspectives to influence decision-making while building trust and effective cross-functional collaboration. Bonus points: You have experience with dbt and data modelling. You'll be working closely with our data team on the curation pipeline that feeds our AI data products. Why AirHelp: Culture of Autonomy: No micromanagement, no politics. Just builders building. Growth Investment: Personal development plans, internal workshops, mentorship, and language classes. Culture That Cares: Team events, supportive peers, and a mission you can feel proud of. Flexible Benefits: Choose between gym pass, personal development, childcare, transport, or travel subsidies. Global Workstyle: Work from anywhere for up to 2 weeks/year, because we know the best ideas come from seeing the world.

Responsibilities

The role involves embedding within product engineering squads to drive data-driven decisions for mobile claims adoption and subscription growth. You will also own the data curation pipeline to power AI-driven analytics and enable self-service for product managers.