Position: Data analyst
Category: Data Analyst
Experience: 5 years | English: upper

Experienced data analyst especialy in marketing analytics with strong knowledge of statistics (ML) & python, databases, BI reporting & visualization. At my last position company started an expansion campaign (users from new geo regions) and I took part in it as a Data Analyst/Engineer/Consultant. Two times I was one of the first specialist on project and built analytics from scratch. My role was to help the User Acquisition Team (UA) make decisions & did marketing analytics in general: formation of high-quality data (in parallel i did a data quality control) in database and in the whole system for building BI reports on that data for providing User Acquisition with the necessary data. All of that was combined and turned it into a high-quality report that is used on a daily basis. Such as predictions (which greatly helped the team in buying traffic) that is, to evaluate the effectiveness of buying traffic: when it pays-off, finding the drops in metrics on the timeline, finding problematic areas and did such recommendations in general what can be improved, in-depth analysis to find some new information which will be usefull for UA. Collected data transformed into a report and it was used not only by the UA, but by the Marketing Team and the Product Team. I faced with a bunch of traffic mediasources, large volumes of users, different data sources.  Also participated in hiring and onboarding an employee for my small user acquisition analytics team.
My full work experience details in CV. Experienced data analyst especialy in marketing analytics with strong knowledge of statistics (ML) & python, databases, BI reporting & visualization.

Analytical part: Statistics, ML, Python (numpy, scikit-learn, pandas, matplotlib), SQL. LTV forecasting, predictive analytics, ML and related operations (data cleaning, EDA, preprocessing, feature engineering, feature selection, model selection, cv & tuning, evaluation), choosing a wide number of metrics to achieve best results. Have been making revenue predictions and doing "targets" (target ROI of day N to achieve 100% of ROI at day N) for User Acquisition Team. Calculating a lot of different product and marketing metrics such as: ROAS, Retention, Churn, CPM, CPI, CPA, Renewal Rate, ARPU etc. Research and finding answers in data, search for growth points or problem solving. AB tests.

Database & BI part: Creation of views, tables, schemes (DDL, DML). Used Airflow for ETL. OOP, Functional programming. Advanced in SQL querying (windows, subqueries, CTE and etc) and optimisation of queries. Experienced in ClickHouse, Postgres, Redshift, Vertica, AWS Athena & BigQuery and understanding of their work and DWH in general. Data visualisation and dashboards, reports creation in Redash, Tableau, Superset and internal tools (in Appsyoulove). Also work in Tableau Prep for creating data source flow. I know how to handle API, otherwise I can do web scraping.

5 years experience
Apr 2023 - Present
Data Analyst | Consultan - Repeatt
Warsaw, Poland
Startup where I occasionally help set up data analytics (ETL, BI, reporting). I participated in connecting amplitude, BigQuery to amplitude, setting up events, analyzing user behavior, AB tests through firebase and analyzing them in BigQuery, LTV forecast.

Mar 2022 - Apr 2023
Senior Data Analyst - GR8 Tech
Kyiv, Ukraine
I ran a long-term project in marketing analytics from scratch. Parimatch started an expansion campaign and I took part in it as a data analyst/engineer/consult . The achieved end goal: to help managers who buy traffic so that they can make decisions based on data.

Sep 2020 - Feb 2022
Data Analyst | Marketing Data Analyst - APPSULOVE
Kyiv, Ukraine
Achieved goal: marketing analytics from scratch. Predictions and wide variety of product & marketing metrics to make a decisions based on gathered data which converted into a report that were used by whole UA Team to daily buying new traffic, users
I prefer to automating everything and establishing analytical processes but I am open to any suggestions so I will consider any data-related work (such as Data Analysis, Data Science, Data Engineer).