Position: ML Engineer
Category: Data Science
English level: fluent
Years of experience: 4

- performed end-to-end ML pipeline for vehicle test assistance in automotive
- proven recommendation from Project Manager at Google
- proven as an independent combat unit at complex projects, which I handled for clients myself only
- developed a promotion algorithm which still serves the company faithfully for 3 years already
- AI Engineering for voice processing
- End-to-end ML Engineering in automotive (vehicle test assistance app)
- AWS Ecosystem (Glue, SageMaker, Lambda etc.)
- GCP (BigQuery, GCC, 


Python Stack: Pandas, NumPy, Flask, BeautifulSoup, Scrapy,
Selenium, Matplotlib, Seaborn, SQLAlchemy
ML Stack: Tensorflow, Keras, Scikit-learn, SciPy, XGBoost,
LightGBM
Dashboarding Stack: Tableau, Google Data Studio, Niche
Dashboarding
Databases: Oracle SQL, PostgreSQL, SQLite, BigQuery, MySQL
Notebooks: Jupyter Notebook, Google Colab
DevOps Stack: Docker, Google Cloud Composer, Terraform
Orchestrators Stack: Apache Airflow
AWS: SageMaker, Glue, Lambda, S3, SNS/SQS, ECR, ECS, RDS, EventBridge