lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist
Category: Python
Experience: 3 years | English: upper

* Development of a Deep Learning model that accurately predicts rooms for the given floorplan.
* Electronic Design Automation routing tool that managed to decrease the overall parasitic capacity of routes made by human or by other software tools that made routing based on the shortest path idea.
SUMMARY
Python developer with a decent background in web development and applied physics that is passionate about physics and technology and wants to expand his knowledge in Data Science and Machine learning.

PROJECTS
* Developed and deployed a DL model that makes automatic price estimations for raised floor projects based on the uploaded blueprint of a floor plan. 
Currently working on a similar project for the door industry.
(PyTorch, FastAPI, Azure/GCP)
* Managed the project for HR community, where the data from social media was processed by NLP models.
(Django, Azure, spaCy/Transformers)
* Took part in the development of pen-source Exonum project.
(Rust, Python)
* As a member of the research team took part in the development of Electronic Design Automation tools for integrated circuit routing.
(Python, C++)
I would like to be a part of a research team that works on solutions that involve machine learning.
Also I would be glad to work in a medium-sized team that works on a product.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

I have completed the course of Data Science and have work experience as a Data analyst
-System analyst 1 year
-BPM Developer (Corezoid) 1.5 year
Currently, I want to change the work direction from analytics to data science.
I have experienced during Machine Learning (90h, individual) courses in:
 - building machine learning models for solving classification, clustering, regression problems
 - collecting, processing, cleaning data for modeling
- data visualization
- outliers detection
- time-series analysis
- SQL scripts
Position: Data Scientist
Category: Data Science
Experience: 7 years | English: fluent


Tasks accomplished:
- human motions classifier,
- price recommendation system,
- text classifier (NLP),
- fraud detection.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Certified data Scientist endorsed by Data Science Academy
Financial certificates
Technical Skills:
- Data analysis: Python, SPSS, R
- Data visualization tools: Tableau, Power BI desktop, Power BI Report Server, R, Excel
- Programming Languages: Python, R, SQL-Oracle
- Machine Learning: Regression, Classification, Clustering, Time-series, hyperparameter tuning, Pipeline modelling, Boosting, Bagging. 
- Deployment tools: Streamlit, Django
- Deep learning: Pythorch, FastAI, OpenCV, Computer Vision,  NLP, Tensorflow.
- Additional: Due to financial background, strong understanding of company stuctures, types of contracts, presentation formats.

Soft Skills:
- Out-of-box thinking
- Fast learner
- Leadership
- Management
- Critical thinking
- Solution Orientation

Last two work experience:
Reporting Specialist
Umid Babek Operating Company (SOCAR)
2022 - Present,
Responsibilities: 
- Preparation of full company management report.
- Collecting past and present data, analyzing collected data, finding correlations between variables, using BI tools to visualize data in most relevant form, finding ways to improve operations and reduce costs, planning and managing projects on implementation modules of SAP ERP.

Reporting Specialist
Azerbaijan Airlines
2021 - 2022,
Being a part of Reporting team established and implemented strong Reporting system. Preparing yearly, quarterly, monthly Management reports, analyze, make suggestions on identified
inconsistencies and problems.

Data Science experience examples:
Image classification with Python (2022)
Given the Image Classification dataset consists of 6 classes, I am asked to build a model that can correctly classify images. I applied a method called transfer learning and tried three neural networks architectures: VGG16,Resnet50 and Inception-v3 Build a neural model that can classify with 92% accuracy. 

Data Cleaning on Electricity Usage Data with Python (2022)
In this project i have been provided with data of Electricity Provider Company. As data was in a unstructured and unsorted format i had to clean data and turn it into usable format. My second task was select optimal contract based on usage history.

Kaggle Tabular Playground Series (2022) - Used Prophet time series analysis to predict book sales of 4 country and 6 product name. Evaluation: SMAPE: 12.29
- Strong vision of company.
- Provision of work environment in which I can contribute to the team, I receive appreciation for my contributions, I have job stability and the ability to grow with the company.
- Position that will allow me to put my talents and expertise to good use while still allowing me to develop professionally and personally with the business.
- Personal development Plan for workers.
- Understanding Team leaders.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper


Technical stack:​ PyTorch, TensorFlow, OpenCV, Pillow, Numpy, Pytesseract, Pandas, Plotly, Matplotlib

Main areas:
- Machine Learning(supervised, unsupervised), 
- Deep Learning(Keras, Tensorflow, PyTorch), 
- Python(numpy, scipy, scikit-learn, pandas, etc), 
- Data Visualisation(matplotlib, plotly), 

Research project:
Real time visual speech synthesis: studying influence of future context for coarticulation modeling. It was
investigated how the Bidirectional Gated RNN performs face articulation of French and German languages with
range of future context information.

Final project:
Detection and recognition of text on images from social networks. The project pipeline consisted of several
stages. Pre-processing, searching for areas with text in the image, cropping and correcting the angle,
recognition of the text, evaluation of the result based on the created metric.

Currently, I’m deeply involved with machine learning and mathematics approaches.
It is pleasure to work with a lot amount of data and building models for mathematical description of dependencies of these data. But I prefer projects, which could make better usual life using Computer vision or NLP, it is interesting and its encourage me to work more )
Position: Data Scientist
Category: SQL
Experience: 11 years | English: basic


Technical support of banking systems.
 Development and application of software in Delphi programming language for automation of treasury processes.
Create automation system for "Ravan Sigorta" company using Oracle DB and Delphi.
Develop bank system with C# and Oracle DB.
Built a Data Warehouse from scratch.
 Collection of business requirements, provision of database design and architecture, job creation through ETL (SAP Data Services Designer).
 DWH data migration from Sybase to Oracle.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: fluent

Please, check my Github repos:
.../serguzz/DataScience
.../serguzz
---- Tech Summary ----
Please, check my Github repos:
.../serguzz/DataScience
.../serguzz

• Python, numpy, pandas, scikit-learn, Anaconda, Jupyter-Notebook
• PHP 8.0 (native, Laravel, Composer), JavaScript (NodeJS), MySQL. Plans: Node.js (Express, Nest), Vue.js
• Git/GitHub, Docker/Docker-Compose
• Linux (Ubuntu), Windows

April 2023 - till now: Python, Data Science, Machine Learning: Predictive modelling of time series.

Oct 2021 - till now: PHP Developer-debugger, 3rd line support . Database analysis, Log analysis, Network analysis, coding-debugging, business logic analysis, bug reporting, bug fixing, refactoring, proposing solutions; Tech stack: PHP, Java, Javascript, MariaDB, Grafana, Kibana, Github, IntellijIDEA. 

May - Sept 2021: Full stack developer: Building from scratch and deploying travel agency web site. Tech stack: native PHP (MVC pattern, routing, etc.), MySQL, REST API endpoints, Ajax (pagination); based on a responsive design pattern at the frontend. 

Pet projects: - Developing online e-shop using Laravel (PHP, composer). The site contaied pages of goods, categories, user registration, Cart, etc. - Developing blog, using Vue.js / Node.js / Nest.js - Building REST API with authorization (JWT) and documented with Swagger. Based on Nest.js 

Hobby:
Blockchain/crypto: Fundamental analysis of blockchains, crypto projects, ecosystems, partnerships. Studying related news, social media.
Data Science with Python
Machine Learning
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: upper


- text summarization(transformers, autoencoders)
- recommender system( matrix factorizations and NLP)
- topic modelling(LDA, Gensim)
-NER
-sentiment analysis
- outliers detection(text)
- different ML algorithms on top of table data
My goal is to find project where I could improve my skills and get new one's. Solve everyday  challenges with a clean code.
Position: Data Scientist
Category: Python
Experience: 1 years | English: pre

Functional AI library on java.
Reinforcement learning agent for play the games("snake").
Work with computer vision systems.
The creation of a system of electronic journals for teachers of one's own university is a thesis.

Creating your own deep learning functional library in the java programming language.

Work with TensorFlow and Pytorch libraries to implement own projects.

Development of artificial intelligence systems for solving the tasks.
I want to work with AI, develop my own skills and discover new things
Position: Data Scientist
Category: Data Science
Experience: 11 years | English: fluent

1. At my last job: the decision making algorithms I created are implemented in production and help to detect mobile install fraud automatically.
2. At my job at eScore Technologies:  developed new bookmaking strategies and investigated them via statistical simulation. The strategies potentially allowed to reduce bookmaker's risk significantly.
3. At my job at the Institute of Radio Astronomy: Has developed new observational strategies for  statistical data processing at the world-largest radio telescope UTR-2. Implemented them into production code in C on Linux platform. These allowed to extract principally new information
from the observational data.
The last job: Senior Data Scientist at Scalarr since August 2018 to April 2020. Developed anti-fraud algorithms
for fraud detection, data exploration and visualisation. Constructed customized statistical indexes for
compact description of large datasets. Implemented the algorithms in Python + SQL on Linux platform.
The algorithms made it possible to detect and explore potentially new types of fraud and to reduce false
positive decisions via rigorous taking of statistical significance into account. Algorithms successfully
work in the production code. Also consulted team members on applied statistics and probability.

The job of interest unites: machine learning, statistics, programming/scripting
1. Makes it possible for me to apply my passions and talents: machine learning, programming, statistics
2. Requires non-standard approaches and tailor-made methods, not a routine reiteration of the same methodology.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper

At the last place of work, I did an algorithm for a prototype with a scratch. It's always interesting to start from zero to make something new, particularly in scientific research. 
I took part in some IT conferences and made a presentation about the work results.
The main projects are:
1. Moscow streets noises classification (2017), the goal was to classify input urban noises onto one of the several categories (people noise / train noise / construction noise / etc).
2. Map with marked people patterns predictions (2018). The main task was to merge some metrics between several maps' layers in order to build the whole map with which we could be able to predict users' behavior patterns during the Football Championship 2018. 
3. Human faces real-time detection (2018). I needed to use neural networks with pre-trained weights in order to make some real-time faces recognitions for age and gender predictions. 
4. Object parameters estimation (2018). Under the NDA, I can only say it was related to digital signal processing and I used some SOTA radiolocation algorithms to do that. 

Also, I have learned some NLP scientific work at the university and will be glad if the project will look a little bit similar. 
The main interests: computer vision and NLP as well as information retrieval (IR).
I love small companies, because the contribution of each of its members is more valuable. Also I prefer R&D instead of industry development. 
I don't want to engage in advertising, marketing and finances.
Preferred areas: natural language processing, computer vision and information retrieval.
Position: Data Scientist
Category: Data Science
Experience: 10 years | English: intermediate


- Theoretical background in statistics, algebra, and calculus with a broad range of computer experience.
- High proficiency in machine learning, data mining, math modeling and data visualization.
- My ML stack: Python, Pandas, Scikit-Learn, Tensorflow, Jupyter, etc.
- Machine Learning experience: Computer Vision, Deep Learning, NLP, Imbalanced classification, Anomaly detection, Regression, etc.
I want to apply my math and computer science skills on challenging tasks. More science, less routine.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


There are some projects I have worked on:
1.	Using Python and data manipulation and visualization tools (pandas, Numpy, Matplotlib, Seaborn) for data preprocessing and researching the epidemiology of temporomandibular disorders in Ukraine.
2.	Implementing automatic products data collection from websites, aggregating data about products representation and availability in social networks, online stores, offline stores, creating sales analysis reports, collecting product reviews for further response strategies for customers feedback.
3.	Taking part in website development with cryptocurrency trends, exchanges, etc. using Python 3 and Django framework. Working with relational databases (PostgreSQL). Getting data using RESTful API and web scraping with Beautiful Soup library. Working with Pandas, NumPy, Matplotlib for aggregating data and preparing analysis reports.
4.	Strong mathematical background (MS in Applied Mathematics).
I prefer long term projects with a passionate team, because I like to see my contribution to it, so product company would be nice.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper

1. Created a deep learning model and deploy it using Flask. This model can classify dog breeds.
2. Created ML model, that predicts breast cancer.
The set of skills that I have learned in my projects:
1. ML Models creating using Python (classification prediction)
2. Creating visualizations and exploratory data amalysis.
3. DL models creating using Keras(Python)
I am open for any offers:)
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent

Once I was loosing a tournament tennis match 0:6, 1:5, 15:45 and somehow managed to turn it around - 0:6, 7:5, 6:0.
(Former professional tennis player)
Things I do (data science):
Spatial Data models for retail industry.
Models for marketing communications (e.g., feature engineering from text/image + prediction model).
ETL, robust pipelines, automated reporting etc.
Communication of the project/results to customers and internally.
Tech: R, Python, Docker, s3, Parquet, git.

Things I do (research, marketing science):
Network models, Consumer behavior, Bibliometric analysis, Science of Science, Scientometrics.
I love my current data science position a lot, as we have crazy good team and a great opportunity to develop different skills. I was doing a PhD and full data science position simultaneously, and now PhD is done. So, I am open to fill some time with more interesting work.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: fluent

-- Masters degree in telecommunication engineering;

-- Udemy Specializations:
    - Workshop in Probability and Statistics;
    - Deep Learning with TensorFlow 2.0;
    - Python for Finance: Investment Fundamentals and Data Analytics;
    - Building Recommender Systems with Machine Learning and AI;

-- Kaggle courses:
    - Geospatial analysis;
    - Machine Learning explainability;
    - Deep Learning;
    - Feature engineering;
    - Data visualization;
    - Intermediate Machine Learning.

-- Kaggle competitions:
- Top 3% Housing Prices Competition.
- Top 29% Predict Future Sales.
-
- This summer mostly spent on Kaggle.com competitions. Achieved top 10% in some cases.

- Helping with data analysis in medical project. Basically made sure the data produced as a model predictions is human readable and leads to conclusions.

- Produced feature engineering and classification machine learning model for diagnostic project.
I am looking for a team, where I would be able to develop my skills in such directions:

- Deep Learning (LSTM, RNN, computer vision).
- Machine Learning.
- NLP.

It would be great to work on a technology that might change the world.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate


Throughout my career, I have acquired comprehensive experience in managing and maintaining data integrity, quality, and governance. Working at ITALDİZAİN as a Data Steward, I diligently ensured the accuracy, completeness, and reliability of the company's valuable data assets. My responsibilities included data profiling, data cleansing, and establishing robust data quality frameworks.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent


Throughout my career, I've been involved in the development of multiple machine learning products for organizations of different sizes and domains. I mostly specialize in classic machine learning and computer vision (with deep learning). 

Projects I've worked on:
* Internal automation products for large online retailer
* Sports highlight generation service
* Recommendation system for ad bidding platform
* Time-series modeling for gaming company
Not interested in data engineering positions.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: upper

With my assistance, the company automated its work process and reduced the time of processing customer applications from 10 min to 30 sec with an increase in general profit.
I've designed and implemented the ML and MLOps systems from scratch. They are being used in commercialized production applications right now. Looking forward to working on interesting projects that might include ML and possible MLOps integrations!
Throughout my Data Science career, I've worked on several different projects that included the realization of programming skills as well as leadership skills. The most impactful ones:
1. Designing a ML approach for the system of analyzing bank transactions: building a data labeling app, training a ML model, deploying and monitoring the best version.
2. Building ML pipeline for credit risk scoring and converting it to the MLOps pipeline using GCP and KubeFlow on top of the Kubernetes cluster. Automated continuous training and monitoring of versions of the models.
Main stack of technologies: Python, pandas, TensorFlow, Keras, PyTorch, XGBoost, GCP, KubeFlow, Docker, Power BI
Looking forward to increasing my skill in MLOps by building and designing ML pipelines for different commercial projects.
Position: Data Scientist
Category: Data Analyst
Experience: 1 years | English: upper


Throughout my experience, I have been involved in diverse projects that have significantly expanded my analytical and technical skills. As a Blockchain Analyst at a hedge fund, I conducted in-depth research on blockchain technology and cryptocurrencies, analyzing decentralized protocols across various blockchains. I developed new databases and automated cryptocurrency price updates, utilizing Python and Excel. Additionally, I explored trading technologies and analyzed indicators to identify correlations between crises and the cryptocurrency market.

In my role as a Junior Data Analyst at Coral Travel, I collaborated with analytical and sales teams. My responsibility entailed processing and formatting data to adjust service prices. For this purpose, I utilized Excel and other data analysis and processing technologies.

Currently, I am actively pursuing the enhancement of my knowledge and skills. As a Data Analyst, I leverage my analytical and technical expertise to extract valuable insights from data. I am deeply interested in exploring new data analysis methodologies and working with complex large datasets. My next step in professional development involves delving into machine learning and artificial intelligence to create more accurate and predictive models based on data.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

- semi-finals in "The A.I. Guardians" international competition held by Microsoft (project - Smart Teacher Assistant: Automating teacher assistant's work like grading, q&a, recommendations)
- Updating existing Research Paper within KAIST class for MS and PhD students (Expressive Real-Time Intersection Scheduling) using Reinforcement Learning
1st place in Hackathon held by MOST and Unicef (project - vaccination analytics)
- 1st place in local Kaggle competitions within Yessenov Data Lab (Pokemon classification)
- 1st place in local Hackaton (case - PedestrianTraffic Control in streets -  Computer Vision)
- Part of Olympic Training Center within my university (preparation for ACM ICPC)
- Took part in fraud investigations within Digital Crimes Unit team at Microsoft. Built a repository-type environment with functionalities like HDBSCAN clustering, force-directed graphs (networkX) and SSDEEP fuzzy hashing for investigators using Azure Machine Learning platform. 
- Conducted a clustering analysis on large amount of phishing kits (3 mln zip files) using Azure Databricks platform and Apache Spark framework. Dealt with Big Data in Cloud. 
- Built a Image Pdoto DNA hash clustering algorithm that outperformed previous technique (prediction of single hash from 5 hours to 1 second). 
- Applied Deep Learning (LSTM) and Optical Character Recognition algorithms to classify pdf documents.
- Analyzed large amount of traffic data from biggest cities in Kazakhstan (10mln rows per month) and built a vehicle movement simulator using Plotly.

I want to improve my leading skills as well as my hard skills which include projects involving Reinforcement Learning and Deep Learning. Classic Machine Learning is also very interesting for me, if it involves making state-of-the-art solutions.
Power BI is not something I will do very productive. I have an experience with it, but I don't  have much interest to deal with it
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper


Took part in improving algorithm for suggestion similar clothes, also developed computer vision model based on YOLOv5