As a member of the BI team I have been working on multiple data-related projects and my main responsibilities included:• development, maintenance and data quality assurance of a project with the purpose of serving new data points to business stakeholders• data cube migration - creating and owning the data quality and reporting• performing adhoc or long-term analyses for various stakeholdersMain software I have been using is Teradata (SQL), Excel, Python and Kyvos.

Main tasks and responsibilities include maintaining and creating reports and tools for gathering and visualising customer insights - analysing user behaviour in internal websites and applications - with belief of improving the service effectiveness and customer experience where needed.Another segment I was included in is survey analysis - mostly in order to find out customer's opinions and identify potential pain-points. Surveys are designed in Qualtrics and I would provide support on both data modelling and visualisation side. Using primarily Python and it's libraries for data handling. Out of advanced analytics topics - NLP techniques were the most frequently applied in our team.Other part would be typical ETL work - querying various types of databases and creating (maintaining) data pipelines.Finally I would provide advisory and collaborate with colleagues from other fields, e.g. UX/CX, IT or HR.Software/tools used:• Python (JupyterLab) - pandas, numpy, matplotlib• Tableau• Oracle, MSSQL, Denodo• MS Office products

Responsibilities include: • development, maintenance and improvements to both scheduled and ad-hoc database processes• data quality and logging for the above• creating reports and visualisations for management and other teams• churn prediction modeling• general analytical supportTools and software:• PostgreSQL• RapidMiner• Kibana & Elasticsearch• Ruby on Rails• SuperSet (former Caravel)• git

As a part of a Business Intelligence team in Marketing Services department, my work responsibilities included:• creating analyses for internal purposes as well as client based ones• adjusting the main data pipeline including tuning the model (Naive Bayes classifier)• maintaining the client based ETL processes• providing analytics support to other teams (other aspects of business)• mining the data for interesting/useful information• or using the results for any kind of improvementTo achieve these responsibilities, it was required to use various kinds of, not only, data manipulation/data processing software and database systems. During my time in VisualDNA, I got in touch with:• R• MySQL• Scala• Hive• Hadoop• Python• JasperReports• JavaScript• git

Part-time.My scope of employment was to support the lead analyst by creating reports and analyses using mostly MS Excel and VBA.