Senior Product Data Analyst

ABOUT US Hostelworld Group, the global hostel-focussed online booking platform, inspires adventurous minds to meet the world and come back with life-changing stories to tell.
Our customers are not your average tourists, they crave cultural connection and unique experiences that we make possible by providing an unbeatable selection of hostels in unmissable locations - all in the palm of their hand.
It is the social nature and community feel of hostels and their environment, that enable travellers to embrace journeys of discovery, adventure and meaning.
We have more than 13 million reviews across 17,800 hostels in more than 179 countries, making the brand 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, high-calibre team of 230 people within Technology, Product, Global Markets, HR, Finance & Legal and Marketing Teams across our Dublin, London, Porto, Shanghai and Sydney offices.
Hostelworld is listed on the London Stock Exchange and Dublin Euronext.
You can read more about our story here.
LOCATIONThis role is based in Portugal.
We have 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.
WHO YOU'LL WORK WITHWe have a matrixed structure here at Hostelworld; with Growth teams comprising of people across Technology, Product, Marketing and Analytics & Insights (A&I) - all working towards one common goal with aligned objectives.
This role sits in the Customer Analytics Team reporting to the Head of Customer Analytics.
We are looking for a seasoned Senior Product Analyst with a strong focus on data-driven product enhancements and a background in machine learning.
The ideal candidate 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.
This role is suited for someone with 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.
Our core data stack:
Front End Tracking:
Google Analytics CDP:
Segment CRM:
Iterable Data Storage:
GCP & Snowflake Data Visualisation and Usage:
Tableau, Snowflake, Vertex AI Orchestration:
Airflow Transformation:
DBT Synching data:
Fivetran, Hightouch, Twilio Segment WHAT YOU'LL DO 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.
Lead the integration of machine learning insights into product strategies, ensuring that data-driven decisions align with user needs and business objectives.
Develop comprehensive data analysis frameworks to monitor the health and performance of the recommender systems over time.
Spearhead A/B testing strategies and other experiment designs to continually validate and iterate on the machine learning models.
Translate complex machine learning concepts and outcomes into actionable business insights for cross-functional teams and stakeholders.
Stay abreast of industry trends, technologies, and competitive strategies in machine learning and recommender systems to maintain and boost innovation.
WHAT WE'RE LOOKING FOR Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Math, or a related field.
5+ years of experience in a product analytics role with at least 2 years focused on machine learning projects, preferably with recommender systems.
Strong analytical skills and experience with programming languages such as Python or R.
Proficient in SQL and familiarity with big data technologies such as Hadoop, Spark, or similar platforms.
Demonstrated ability in using data visualization tools like Tableau, Looker, or similar.
Excellent problem-solving abilities and experience structuring and conducting complex data analyses to support business decisions.
Effective communicator capable of explaining complex data insights and concepts to non-technical stakeholders.
WHAT WE OFFER Competitive salary & benefits Enhanced annual leave plus 3 Wellbeing Days per year Paid family leave (maternity, paternity, surrogacy & adoption) Agile working (plus a Working from Abroad Policy!) Support for your ongoing growth & development Inclusive people policies (sickness, menopause, compassionate and fertility leave) A chance to give back to your local community with 5 paid volunteering days OUR BEHAVIOURS Grow others- We fundamentally believe that investing in growing others benefits everyone, whether it's helping them develop hard or soft skills.
We want learning and growing to be part of our DNA to help makes us a better team, together.
Master it - We are obsessed with our area of expertise and enjoy developing our skills.
We rarely take things at face value; we investigate, interrogate, and always look for 'the why,' and wherever possible, we use data to find the best solution.
Collaborate - We are in it together, for the tough stuff and the celebrations too.
To achieve the best results, we need expertise from all areas of the organisation, and we wholeheartedly welcome diverse thinking.
Adapt - We work fluidly, adapting to new information and the evolving environment while staying committed to our goals.
Innovation and experimentation fuel our projects and we're never afraid to pivot.
Deliver - Our focus is always on the end result; we value outcomes over activity.
We collaborate to deliver work at speed without dropping any of our other behaviours.
We believe in talented and diverse teams that reflect the diversity of our customers and the communities in which we operate.
Everyone brings different perspectives and experiences.
We lay out the above requirements to guide applicants to the experiences that we believe will allow you to be successful in the role.
If you don't meet them all, please consider applying if you think you can still perform the role as described.
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