Position: Middle Data Scientist
Category: Data Science
English level: upper
Years of experience: 2

- Development of production-ready CPM prediction model (including architecture idea, data gathering, data preparation, evaluation and automatic retrain pipeline)
- Improvement of CTR / EPC classification models (feature engineering and retrain optimization)
- Improvement of the spam comments classification model by designing new features and evaluating their impact
- Customer base segmentation using cluster analysis
- Image similarity research (using classical hash functions and neural networks)
- Certificates in Deep Learning, Recommender Systems, and NLP.
I am a Data Scientist with 2 years of experience as a DS and 7 years of overall analytical experience. Key responsibilities: modeling, feature engineering, data preparation, data analysis, documenting, and communication with the stakeholders and tech team.

Job experience:

Apr 2022 - Present:
Data Scientist
- Creation of production-ready CPM prediction models (regression problem)
- Improvement of existing models for CTR / EPC prediction (classification problems)
- A/B testing new models to reveal the best solution
- Research and implementation of different approaches to solving customers' problems.

Stack: 
Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, CatBoost, Tensorflow, Keras, Shap, Requests, Amazon S3, Vertica, Tableau, Gitlab, Jupyter Notebook, PyCharm, MLFlow.

May 2021 - Mar 2022
Data Scientist, Rozetka.ua
- Classification of spam comments (using XGBoost)
- Customer base segmentation (using cluster analysis)
- Research on the similarity of images
- Analysis of user behavior.

Stack: 
Python 3.8, Pandas, Matplotlib, Seaborn, Scikit-learn, XGBoost, Featuretools, PySpark, Imghash, GCP, Clickhouse, Git, Jupyter Notebook, PyCharm.

Jun 2020 - May 2021 
Data Analyst, Rozetka.ua
- Development of reports for the BI system
- Analysis of the company’s KPIs
- Creating business requirements for tech specialists to organize and tune ETL processes.

Stack: 
ClickHouse DB, ReDash visualizer.

May 2008 - Oct 2012 
Data Analyst, Vodafone Ukraine
- Micro-segmentation of the customers base (cluster analysis)
- Assessment of the impact of changes in charging and service on the user behavior
- Automation of marketing campaigns launch (SQL scripts for Big Data)
 
Stack: 
SAS, MS SQL, MS Excel, pivot tables.
- Career growth opportunities in the area of Data Science / Machine Learning
- Dedicated time for learning new ML technologies
- Friendly team
- Remote job.