Position: Data analyst
Category: Data Analyst
English level: pre
Years of experience: 8

Building a reporting system from scratch (client analytics), automation.
Segmentation (life cycle, RFM, cohorts) and clustering of the company's customers (consumer preferences).
Implementation of predictive models (sales volumes of products, customer scoring).
Conducting research analyzes, the insights obtained from which made it possible to set up monitoring of new metrics, reduce losses, and increase income.
I have 8 years of experience as a data analyst in a large retail (Eva), telecom (Vodafone), service company, betting.
Research tasks to find useful business insights, possible points of growth, and loss reduction. Building dashboards in BI tools, ensuring their performance.
Database: BigQuery, AWS (S3, Athena, Redshift), Oracle PL/SQL, SAS (SQL + Data Step), SQL Server, PostgreSQL.
Knowledges in database theory.
Data visualisation tools: QlikView, Power BI, Metabase, Tableau, Superset.
Python, R - processing, data transformation, visualization, clustering, forecasting, building
association rules, algorithms based on decision trees.
Apache Airflow. Support ETL / ELT processes.
Version control system: GIT.
Microsoft Office: Excel (with VBA, Power Query, DAX), Power Pivot, Access, Power Point,
Word.
Experience with large data sets (> 1 million rows). Knowledge of the theory of probability and
mathematical statistics, random processes, numerical methods. Construction and application of
mathematical models (including machine learning).
Job responsibilities should be related to both data analysis (possibly data engineering) and building machine learning models.