Position: Head of Analytics/ Lead Data Analyst / Data Scientist / Data Engineer
Category: Data Analyst
English level: intermediate
Years of experience: 11

- easy-to-manage analytical processes with reusable results and code, knowledge sharing, and customer focus
- data-driven approach
- the central data warehouse data model author
- development of light wear ETL command-line tool
- BI replacement approach based on google sheets
- classic ML feature engineering approach based on Weight of Evidence (classic bank scoring technics)
- ML models (credit scoring, churn prediction, fraud detection, deal detection)
Worked with different data sources and business processes in a wide range of contexts and roles, from high-level strategy, and roadmap to day-to-day tasks. In Banking (15 years) and E-commerce (6 years).

- Data  integration, processing, cleaning, ETL
- Data Warehousing and Data Lake concept implementation
- Postgres, PrestoDB, ClickHouse, Oracle, Teradata, MS SQL, MS Access, MySQL, SQLite, MongoDB, Couchbase, Spark/Thrift
- SQL knowledge, procedures, functions, usage of analytical and window functions, development of agreement of usage names. Author of central database model in warehouse project. 
- Programming in Python (command line interface tools, web applications, data crawlers, data analysis notebooks)
- Strong in classic machine learning tasks like churn, scoring, and fraud detection (pandas, scikit-learn, IBM Modeler/ SPSS Clementine, SAS enterprise miner) also could work with part of NLP tasks
- BI tools and spreadsheets for building reports (Google spreadsheets, Looker studio, MS Excel, Tableau, Oracle BI, Power BI, Qlik, etc)
- Leaded teams of up to 10 people

I want to find a job related to data/data science area, where, on the one hand, there would be useful and could apply my old skills, but also where there is an opportunity to learn new approaches, learn new tools, and technologies, solve a new type of tasks.