Product: SERP
SERP (Search Engine Results Page) is the search results page team that helps users choose the right flight ticket. What does "right" mean? The cheapest, with no layovers, at a convenient time, without visas, or via a specific airport? We help answer these questions directly in the search.
We help users quickly navigate through a large number of options and make decisions: we improve ticket sorting using ML models, speed up search, and select filters for specific scenarios. Here, analytics directly influence both user experience and business results.
SERP has two teams — Results and Ticket. Together, they are responsible for how users see and compare search results.
Results is responsible for how the search results page is structured: for displaying results, filters, categories, and everything that helps find a suitable option faster.
Ticket is responsible for the ticket card: it makes it informative and helps users compare offers, choose a provider, and the necessary additional options.
We are looking for analysts for both teams — Results and Ticket. Depending on your interests and experience, you can focus on the search results page, the ticket card, or the intersection of these tasks.
What you will do
- Conduct a full cycle of A/B tests within the product: assist with design, select metrics, evaluate results, and formulate decisions based on the outcomes;
- Find new hypotheses in data and user behavior, including from A/B test results;
- Conduct in-depth research into user needs and the reasons behind their behavior;
- Formulate tasks with the product team, think through metrics, and evaluate the impact of new features on the product;
- Identify growth areas, understand where and why the product is not working as expected, and propose improvements;
- Develop dashboards and automated monitoring of product metrics, monitor data quality, and help the team notice changes and anomalies in a timely manner.
What we expect from you
- Experience conducting A/B tests from hypothesis formulation and metric selection to result interpretation and decision-making;
- Understanding of product metrics, funnels, and the connection between analytical conclusions and user/business impact;
- Good understanding of mathematical statistics and the ability to apply it to real product tasks;
- Deep knowledge of SQL: complex queries, analytical functions, and independent data work;
- Experience analyzing real data using Python and the readiness to independently work with data when necessary, not just with ready-made data marts;
- Ability to clearly visualize data and explain conclusions to the product team and other stakeholders.
How we work
- from anywhere in the world: we are not tied to a location, we pay in dollars, and we love to travel;
- no bureaucracy: convenient processes, horizontal and open communication, quick discussion of ideas and decision-making;
- compensation: voluntary medical insurance (DMS), psychotherapy or foreign language courses, sports activities, and sick leave;
- on a paradise island: you can work from Phuket with an ocean view.
