We are looking for:

Data Analyst

Here, at Business-Class, we strive to become the number one choice for all premium-class travelers. A mission we won’t be able to achieve without the right people working together hand-in-hand to accomplish the same purpose. We are dedicated to providing the very best product paying detailed focus on the customer service and satisfaction in order to gain loyal repetitive clients eager to be working with our employees.

We are carefully choosing the best personnel and contribute to their self-development and improvement over the years by providing a great working atmosphere and numerous other benefits:

  • Official employment
  • Initiation and systematic trainings
  • Motivational team-building activities
  • Modern office downtown equipped with relaxing areas and complimentary supplies of water, tea and coffee
  • Flexible schedule
  • Possibility to work remotely
  • Attractive official salary and bonus system agreed individually with the employee
  • In-house and offline events
  • Experience in numerous projects, possibility to improve foreign languages and visit Business Class international offices
  • Career growth opportunities


  • Use data tools to generate insights to drive decision making for various teams (sales, customer support, and marketing)
  • Create and maintaining various team dashboards automated reporting related to key performance metrics to track progress
  • Collect, process, and clean data from disparate sources using SQL, R, Python, or other scripting and statistical tools to identify trends and opportunities
  • Build and maintain data warehouse using tools such as Big Query, Segment, ETL

Requirements and qualifications:

  • 1-2 years of professional work experience
  • Degree in mathematics, statistics, or business, with analytics focus
  • Excellent numerical and analytical skills
  • Knowledge of data analysis tools — you do not need to know all of them at entry level, but you should show advanced skills in Excel and the use of at least one relational database
  • Familiarity with product analytic tools (e.g. GA, Amplitude)
  • Knowledge of data modelling, data cleansing, and data enrichment techniques
  • Experience working with languages such as SQL, R, Python
  • Strong English (verbal and written)