Position: Senior Data Scientist, Tech Lead
Category: Data Science
English level: intermediate
Years of experience: 11

- Development of a software and technical complex for the recognition of audio signals from acoustic emission;
- Development of a system for predicting rock collapses based on the analysis of acoustic waves;
- Development of a global system for long-term forecasting of certain product segments for a large retail chain
SKILLS

Languages:
•	Russian (fluently)
•	Ukrainian (fluently)
•	English (intermediate)
Programming Languages:
•	Python:
•	IDE: Jupyter Notebook, PyCharm etc.
•	Libs: numpy, pandas, scipy, statsmodels, sklearn, tensorflow, keras, matplotlib, plotly, seaborn, sqlalchemy, opencv
•	Frameworks: Django, Flask, MLFlow
•	NI LabView 
•	SQL
•	JS/HTML/CSS (Optional)
•	Scala (Optional)
BI Intelligence:
•	Tableau
•	Power BI
Databases:
•	MySQL
•	Amazon Redshirt (Postgree)
•	ClickHouse
•	Snowflake
DevOps:
•	- Linux bash / Windows PowerShell
•	- GIT
•	- Docker, Docker Compouse
AWS
•	Amazon SageMaker
•	Python SDK
•	Train Models
•	Tune Models (Bayesian optimization)
•	Bath transformation
•	Deploy Models (create endpoints and multiendpoints)
•	Pipelines
•	Amazon Lambda
•	Amazon CloudWatch
*       AutoGluon
Graphics:
•	- Adobe Photoshop CC + Adobe Camera RAW 
•	- AutoCAD

Machine Learning skills
Algorithms used in analyzing tabular data:
•	Logistic Regression
•	Random Forest
•	XGBoost
•	Extra Trees Classifier
•	ADABoost
•	K-Nearest Neighbors
•	Decision Tree Classifier
•	Naive Bayes
•	Linear Discriminant Analysis
•	MLPClassifier
•	LinearRegression
•	ARIMA models for prediction TSA
Algorithms used in pattern recognition tasks:
•	NN
•	Convolution 1D, 2D neural networks
*       Autoencoders
*       Recurrent neural networks, LSTM
*       GAN
*       Genetic algorithms
Business analytics skills
•	identifying the customer's business needs
•	choice of concept for solving the problem
•	drafting and analyzing business requirements
•	conducting A / B tests
•	Identifying the main KPIs of the business and drawing up a hierarchy of the main metrics
•	Implementing machine learning methods in business to reduce maintenance costs and increase profits
•	detailed analysis of business processes for various business segments
•	creation of readable interactive presentations in BI systems (Tableau, PowerBI)
•	- implementation of python scripts into BI systems to solve complex problems

Digital Signal Processing skills
1D acoustic signal analysis:
•	digital signal filtering: FIR filter, IIR filter, z-transform
•	spectral analysis: DFT, FFT, WFT
•	wavelet analysis: CWT, DWT
•	approximation, interpolation, extrapolation, autocorrelation analysis of signals
•	fractal signal analysis
•	Prediction: CLP, AR, MA, ARMA, ARIMA 
2D graphic signals analysis:
•	most of methods from "OpenCV" library
Preferences:
- tabular data analysis
- audio data analysis
- forecasting tasks (purchases, sales)
- research tasks

I don't want to do the following:
- NLP