Position: Product Analyst
Category: Data Analyst
English level: upper
Years of experience: 2

1) Conducted several studies that led to the implementation of local currency processing in South Africa and Nigeria. This helped to diversify the market where our product was present and significantly increased revenue;
2) Conducted the analysis of one of the most large-scale and influential split-tests during the existence of the project, in which a big and totally new feature was added to the product. This had a dramatic impact on our financial metrics at first, so with the help of many people I had to refine the test many times before it eventually showed an increase in revenue and conversions.
Product Analyst at "QUARKS TECH (Genesis)", September 2021 - present:
1) Full cycle of work with the A/B tests: creating hypotheses, checking coverage and data validity, launching the split, monitoring it, analysing the results, closing the test
2) Writing SQL-queries and alerts, working with aggregations and views via Bitbucket;
3) Creating graphs, sheets and dashboards in Tableau, publishing them online;
4) Monitoring the key metrics and making recommendations for marketing specialists.

Junior Analyst at "Together Networks Limited", January 2021 - June 2021:
1) Analysis of big data, researching important insights and building the strategy;
2) Audit and monitoring of fixed tabular data on a daily basis;
3) Organising the creation, verification, validation and editing of the reports;
4) Assessment of quantitative and qualitative differences between data sources. 

IT Intern at "Philip Morris Ukraine", July 2020 - December 2020:
1) Managing the launch of the project, that improves user experience;
2) Working with SQL-scripts for various purposes and within different projects;
3) Creating an online training course as a part of the team;
4) Testing the sites in different environments.

I want to broaden my expertise in analytics and grow with the product, that I will be working on. As for the skills, that I want to improve, they are the new instruments for visualisation of the data, creating more "working" hypotheses and communicate with all the members of the team in order to understand more deeply how does the product work as a whole.