Senior Product Data Analyst: Innovating Travel Experiences

Há 4 dias


Porto, Porto, Portugal Hostelworld Group Tempo inteiro

About Hostelworld Group

Hostelworld Group is a leading online booking platform for hostels, inspiring adventurous minds to meet the world and come back with life-changing stories. Our customers crave cultural connection and unique experiences, which we make possible by providing an unbeatable selection of hostels in unmissable locations – all in the palm of their hand.

We have more than 13 million reviews across 17,800 hostels in over 179 countries, making us the leading online hub for social travel. The website operates in 19 different languages and our mobile app in 13 languages. Founded in 1999 and headquartered in Dublin, Hostelworld has a growing team of 230 people within Technology, Product, Global Markets, HR, Finance & Legal and Marketing Teams across our offices in Dublin, London, Porto, Shanghai, and Sydney.

Location: This role is based in Portugal, with an office hub in Porto available for those who prefer a hybrid model where you can spend time with colleagues in-person. You will need to be able to commute to our office hub as required from time to time.

About the Role: We are looking for a seasoned Senior Product Data Analyst with a strong focus on data-driven product enhancements and a background in machine learning. You will work closely with our machine learning team to optimise and innovate our recommender systems that enhance user experiences by personalising search results and social connections within our platform.

The ideal candidate will have a robust analytical background, experience in ML systems, and a passion for leveraging big data to drive product success in the travel industry. You will be working with best-in-class technology and within a wider motivated team of data analysts, engineers, and scientists.

Your Key Responsibilities:

  • Collaborate with machine learning engineers and data scientists to define and refine metrics for evaluating the performance and success of recommender systems.
  • Utilise predictive analytics to understand customer preferences and enhance recommendation algorithms.

About You: To succeed in this role, you should have a strong educational background in a quantitative field (e.g., computer science, mathematics, statistics), experience with machine learning and data analysis tools, and excellent problem-solving skills. A salary of approximately $95,000 per year reflects the challenging nature of this position and your expected level of expertise.


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