lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist | Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: upper

- crypto-trading bots (own strategy acc to market data analysis);
- applying ML predictive models in crypto-trading;
- pick-by-voice frameforks experience.
IT Depury Head [10 years]
- data proccessing;
- creating a database architecture;
- database restructuring;
- software development;
- information systems development;
- information exchange between different systems;
- data analysis;
- creating analytical marketing decision-making models;
- email/sms marketing.

Python Full Stack Developer, Product Owner [4 years]
- framework for corporate regression testing;
- reports/statistic/dashboards for corporate testing process;
- scripting warehouse processes for voice recognition system;
- version control, setup comparison/transfer tool for WMS;
- BA/PM/QA responsibilities due to small development team.

Machine Learning in "pet" projects [2 years]
- data pre-processing;
- feature engineering;
- classification;
- clusterization;
- recommendations, ranking;
- model selection & validation & tunning;
- ensemble: voting, blending, stacking;
- natural language processing;
- deep learning.
passionate about ML in medical & crypto industry

10 years of data processing
4 years of python development
now more manager than dev

absorbing ML knowledge last few years to switch carrier track
small commercial experience
require mentor

[!] capacity 4-6 hrs per day (involved to few projects)
Position: Data Scientist | Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: upper


My main duties:
•  Initial data investigation and exploratory data analysis ;
•  Processing and cleaning the data ;
•  Potential models and algorithms selection ;
•  Implementation of data science models and algorithms ;
•  Implementation of evaluation pipeline ;
•  Measurement and improving results;
•  Communication with customer.


 I participated in various projects connected to different data science fields :
• Computer vision : football court lines detection, emotion recognition, face landmarks and hand detection, OCR, goods on shelves classification ;
• NLP : text translation, ServiceDesk tickets classification ;
• Deep Learning : LSTM-based solution for bank clients behaviour analysis.
In addition, I also solved optimization problem for carpets on looms allocation based on different constraints and created 3-page Dash-based platform for different ML tasks (classification, regression, time series prediction). 

Used Tools and Technologies :
Core Competence : Computer Vision, Natural Language Processing
Machine Learning : Logistic Regression, SVM, Naive Bayes, Random Forest, Decision Tree, XGBoost, LightGBM, kNN, Clustering
Deep Learning : Convolutional Neural Networks, Recurrent Neural Networks
Programming Languages : Python, SQL
Tools:  NumPy, Pandas, SciPy, Sklearn, Keras, TensorFlow, PyTorch, Statsmodels, OR-Tools, OpenCV, nltk, gensim, spaCy, fasttext, albumentation, matplotlib, seaborn, plotly.
Don't want to work with russian clients. 
I am looking for new opportunities in a company where I can fulfill my true potential as a Data Scientist. 
I want my projects to be related to Computer Vision, NLP or Machine Learning.
Position: Data Scientist | Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: upper

- Strong math(Deep practical skills in the analysis of algorithms, good practical knowledge in next math disciplines with reference to computer science: discrete math, combinatorics, probability theory, statistics, asymptotic analysis. Great base math knowledge.)
- Deep understanding of fundamental DS/ML approaches
- Understanding of full-cycle DS/ML project serving
Throughout my career, I have gained extensive experience in the field of machine learning, with a focus on classical data science and computer vision. I have worked on a wide range of projects in computer vision, including object detection, segmentation, and pose estimation. My skill set includes classic image processing techniques and cutting-edge deep learning methods. In data science, I have a background in statistics, various machine learning techniques, advanced data exploration, model explanation tools, and deployment strategies.


Technologies which I use:

Engineering technologies stack: Docker, Flask, Flask-Socketio, multiprocessing + multithreading, edge devices integration(Jetson Nano), Windows integration(pyinstaller), PyQt, etc.

Data Science technologies stack: Pandas, Scikit-learn, XGBoost, LightGMB, Catboost, Facebook Prophet, model explanation tools(SHAP, SAGE, eli5, LIME), etc.

Computer vision technologies stack: image processing libraries(OpenCV, Scikit-Image, etc.), object detection and segmentation frameworks(YOLO, SSD, Faster R-CNN, Mask R-CNN, UNET), OCR(Tesseract), etc.

Deep learning technologies stack: Keras, PyTorch, TensorFlow, etc.
I am seeking an opportunity to join a team of experienced professionals where I can contribute my skills and experience while collaborating to make strategic decisions and develop impactful products.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: fluent

Developed a machine learning model that improved customer segmentation accuracy by 20%, resulting in a 10% increase in targeted marketing campaign effectiveness.
Implemented a recommendation system for an e-commerce platform, resulting in a 15% increase in cross-selling and upselling opportunities.
Deployed a fraud detection model in a production environment, resulting in a 30% reduction in fraudulent transactions and saving the company $1 million annually.
As a Data Scientist and Machine Learning Engineer, I have been responsible for developing and implementing advanced analytics and machine learning solutions to solve complex business problems. My role has involved collaborating with cross-functional teams to identify opportunities for leveraging data to drive insights and developing scalable solutions using Python and SQL.

Data Analysis and Modeling: I have performed in-depth data analysis on large datasets using SQL, Python, and other data analysis tools to identify patterns, trends, and insights. I have utilized statistical techniques to create predictive models, develop segmentation strategies, and optimize algorithms to improve business outcomes.

Machine Learning Development: I have developed and implemented machine learning models using libraries such as scikit-learn, TensorFlow, and Keras. I have worked on various machine learning projects, including image recognition, natural language processing, and recommendation systems. I have performed feature engineering, model selection, and hyperparameter tuning to optimize model performance.

Data Visualization: I have created visually appealing and insightful data visualizations using tools such as Matplotlib, Seaborn, and Tableau to communicate complex information to stakeholders and support data-driven decision-making.

Collaborative Problem Solving: I have worked closely with cross-functional teams, including business analysts, software engineers, and domain experts, to understand business requirements, identify opportunities for data-driven solutions, and develop prototypes and proofs-of-concept to validate ideas.

Model Deployment and Monitoring: I have deployed machine learning models in production environments using technologies such as Docker and Kubernetes. I have implemented monitoring and logging mechanisms to track model performance and make necessary adjustments to ensure optimal performance over time.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: fluent


Deep Learning Researcher - Computer Vision 01/2023 - Present

CEDAR | Baku, Azerbaijan

Sign Language Recognition and Processing for Azerbaijani Language to make life more accessible
• Developed CNN, LSTM, and Attention models for Continuous Sign Language Recognition with a focus on 3D CNNs and
Sequential Models (Attention and LSTM), achieving 80% accuracy across over 200 experiments
• Design NLP algorithm for context aware sentence completion in Azerbaijani language
• Collaborating with and overseeing cross-functional teams, including computer vision specialists and sign language experts, to
achieve project goals
• Demonstrated expertise in deep learning and computer vision through successful completion of 4 complex projects
• Tech Stack: Python, PyTorch, TensorFlow, Keras, Transformers, Convolutional Neural Networks (CNN), Long short-term
memory Recurrent Neural Networks (LSTM RNN), ANN, OpenCV, Git / Github, Linux, Mlflow, WanDB


Machine Learning at scale 07/2022 – 12/2022

CEDAR | Baku, Azerbaijan

Researches in the area of Big Data processing with Hadoop
• Set up Hadoop system on several physical devices on yarn and tested it on different machine learning projects
• Leveraged Apache Spark (PySpark and Scala) on Yarn and Kuberenetes to implement highly scalable and efficient Big Data
processing pipelines and decide which one is better
• Tech Stack: Python, TensorFlow, Keras, Hadoop, Git / Github, Kubernetes


Machine Learning Engineer Internship 08.2021

SOCAR GAS STORAGE CONTROL | Baku, Azerbaijan

• Data managing and prediction by utilizing machine learning.
• Tech Stack: Python, TensorFlow, Keras, SQL, Git / Github.

Machine Learning Engineer Internship 07.2019

SOCAR AMIRHANOV FIELD | Baku, Azerbaijan

• Data managing and prediction by utilizing machine learning.
• Tech Stack: Python, TensorFlow, Keras, SQL, Git / Github.


Backend developer and database manager Internship 06/2019-07/2020
• Developing websites, and managing databases.
• Tech Stack: Python, PhP, SQL, JavaScript.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: intermediate


Hello, my name is Dmytro. 
I am a machine learning engineer. Engaged in the analysis and classification of images of moles, identifying potentially dangerous ones. Also, there was an NLP project on Text generation as service to help article editors in online portal. Text and image data labeling.
Also solved the problem of detecting objects in the image using neural networks like yolo, delving deep into the tuning of the model.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 1.5 years | English: upper

-Data Camp participant 
-Scientific publications
-Excellent studying skills
I am a Bachelor of Computer Science. I have experience in several team projects. For example:
-The project consists of the two parts: satellite simulation which simulates the rotation of the satellite and neural controller which take the expected rotation speed of the satellite and return the predicted powers on reaction wheels. In this project, I implement a neural controller that uses a neural network to make the prediction (commercial project). 
-The security system is written in python and based on Raspberry pi which verifies person by face and checks if this person has access to come in. In this project, I train the face recognition model, serialize it and then used this model to recognize people from new images.
-Web service for applying surveys written using React and Firebase. In this project,  I implement user registration, integrate Google maps into web-service, design a page routing  (commercial project). 
Also, I have several scientific publications about AI.
-Сareer growth
-New acquaintances
-Challenging and interesting project
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: upper

Education:
- National Technical University of Ukraine 'Kyiv Polytechnic Institute'​  FICT Computer Engineer - Bachelor's
- National Technical University of Ukraine 'Kyiv Polytechnic Institute'​ PMA Data Scientist - Master's

Hackathons:
- Churn prediction, define if the employee will quit the company (SoftServ) 3rd place.
- System for recommending movies on streaming service (sweet tv) 3rd place.
- Book rating prediction (INT20H) 2nd place.
- Forecasting system for retail (Hack4Retail) 3rd place.

Participant Kyivstar BigDataSchool 2018
I am a Senior Data Scientist with 5 years of experience. I like to solve data science problems in the area of machine learning and analytics. Furthermore, I like to tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. But my true passion lies in creating data science tools and simplifying the business and ML processes.

I love teaching and enjoy the challenge of communicating complex concepts clearly and concisely.

Experience:
- MLOps, development, deployment, testing, experimenting, leading the team, planning
- Designed and created algorithms, built models, prototyped solutions.
- Worked in a team with the Software Engineers, Data Analysts, Data Scientists, and Data Engineers of the Data team, as well as our business contacts (Product teams, Sales, Customer Engagement, Marketing, etc.).
- Proposed innovative use cases (features in the product / algorithms to scale our business);
- Manage data scientists.
- Train former data analysts to become data scientists. 
- Build the ML Solutions (AWS SageMaker, AWS Lambda, AWS Batch, API Gateway, MLFlow, Azure Databricks), Datastore (S3, Snowflake) stack.

Projects:
- Predict likelihood of clicking on the AD by the user 
- Content Recommendation Engine – Recommend posts to users by their views history
- Missing inventory on the shop shelf classification 
- Post content classification (auto-moderation system) 
- Churn prediction
- User segmentation to similar groups by their behaviour features 
- Keyword extraction from post content
- NER – Entity extraction from post content

Past projects:

Regression:
- Forecasting the demand for goods. 

Clustering:
- Motion detection by sensor data.

Recommendation systems:
- Recommended Cold Start Movie System.
- System for recommending the next action (purchase/view) for the user

Computer Vision:
- Counting the number of people in the cinema hall. 
- Recognize identification numbers on the railway carriage.
- Fashion image segmentation.
- Pet photo analysis.
- QR code detection
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 0 years | English: intermediate


I am the author of educational articles in the field of machine learning and data analysis. I want to try to apply my knowledge in a real project, because I believe that this will accelerate my development in this area.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: fluent


I have completed my master's thesis in aeronautics. The project I made took about 2 years. I have developed an airfoil selector for UAV designers during the conceptual design phase of an aircraft. Besides, I and my project team in a different area developed 3 neural network models for breast cancer classification. Currently, I m developing a neural network model for temperature and salinity prediction of the Arctic Ocean with Copernicus satellite data at Denmark Technical University. In the industry, I have attended and worked for a company bootcamp for about 4 months as a data scientist.
Position: Data Scientist, Machine Learning Engineer
Category: Python
Experience: 1.5 years | English: upper

Bachelors’s and Master’s degree in Math, Faculty of Mechanics and Mathematics, Lviv National University of Ivan Franko. 

Successfully passed ML BaseCamp from GlobalLogic.
• description: classic Machine and Deep Learning, Convolutional Neural Networks (LeNet, AlexNet, ResNet, GoogleNet, etc), Recurrent Neural Networks, LSTM, GRU, Transformers, GPT, BERT, AutoEncoders, GANs.
Junior Data Analyst
 • description: work with accountings of foreign companies, data preprocessing.
Junior Sports Data Scientist 
 • description: modelling a sport probabilistic models, risk assessment.
Expectations: working in friendly team, developing innovative software, participation in a startups specialized in Artificial Intelligence and Machine Learning.
Position: Data Scientist, Machine Learning Engineer
Category: Other
Experience: 1 years | English: intermediate

Successfully implemented numerous large enterprise projects.
Over 10 years experience in IT as software developer and team lead. Fluent data manipulation, architecting and processing.
Looking for a BigData projects with DS/ML/AI background.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: fluent

1. Master of Science in Computer Science and Data Analytics * Dual-degree program * Computer science degree from George Washington University, Washington, DC, United States.* Data Analytics degree from ADA University, Baku, Azerbaijan. *  
2. Bachelor of Science degree in Computer Science from ADA University. * graduated with magna cum laude honors (3.82 out of 4.00)
3. Published my first paper during my bachelor studies. * Title of paper: "Training and Evaluation of Word Embedding Models for Azerbaijani Language" * Presented the paper in the 8th Machine Intelligence and Digital Interaction Conference. * Later on published in Springer Nature Switzerland journal 
4.   Developed and maintained various Computer Vision Systems for production including but not limited to Face Recognition System, ANPR System, and OCR software which are currently being used nationwide. I wouldn't distinguish any of my achievements as one above another, but I would say my biggest accomplishment is going fast and steady in my field and hopefully learn and gain even more experience in the next 5-10 years.
* Responsible for the Maintenance of AI Systems that are developed and used by the company.
* Main Contributor for ML projects for the company by employing contemporary technologies in Deep Learning:
 1. Automatic Number Plate Recognition System:
      - Gathered around 30000 images from CCTV cameras and Open Source Datasets
      - Trained Models for Number Plate Detection Software, YOLOv4, and YOLOv4Tiny
      - Used Easy-OCR and MobileNet Classification Model for number plate recognition
  2. Face Recognition Software:
      - Developed RetinaFace model with the MobileNet backbone for face detection and localization.
      - Trained and Used ArcFace model (Resnet-50 backbone) for face encodings
  3. Built an OCR software for Electronic Governance System.
      - Retrained Tesseract-OCR to perform better on custom fonts that are used in the system.
      - Software is Mainly used to understand the context of scanned documents
      - Employed NLP and Data Mining techniques to retrieve text summaries from such documents.
   4. Composed Static Word Embeddings for various uses such as Semantic Analysis, Spam Detection, Text Classification etc.
      - Word Embeddings trained on Azerbaijani language.
      - Gathered data from Various newspapers, books, and novels with overall 164 million word tokens
      - Corresponding paper has been shared in my ResearchGate profile.
My expectation is to be a part of an innovative team where we can work on ambitious projects by experimenting and learning new technologies while being able to effectively exploit our expertise.
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 1.5 years | English: intermediate


Samsung R&D Institute Ukraine (SRK)
Software Developer/Machine Learning Engineer 
April 2019 to present
1) Heart rate estimation by video | Python (OpenCV), C++
-Developing an algorithm pipeline.
-Improving heart rate extracting algorithm.
-Developing tools for dataset collecting/evaluating.
-Creating Python wrappers for C++ code
-Developing requirements for a dataset
2) Activity recognition using accelerometer and gyroscope records | Python (Keras)
-Developing different deep learning models for classification.
-Configuring docker images for training models on the cluster.
-Feature development using different signal processing approaches.
3) Heart rate measurement using PPG, accelerometer, and gyroscope records | Python (Keras)
-Improving heart rate measurement algorithm.
-Feature development using different signal processing approaches.
-Сollecting a dataset.
Looking for
Position: Data Scientist, Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: fluent


- Technologies: Python (pandas, numpy, sklearn, scipy, pyspark etc.), Keras, Tensorflow, Pytorch, SQL (Oracle, Clickhouse), PowerBI, AWS, R, Linux, Matlab, RapidMiner, Git, Jira, Confluence, MS Office (Excel, etc.)
- Data analysis, machine learning, deep learning, computer vision (CV), natural language processing (NLP), statistics, scrum, kanban
- Indicators forecasting
- Improved computer vision (CV) algorithm’s performance by 3 percentage points
- Implemented machine learning and deep learning to NLP task
- Improved machine learning (ML) algorithms (regressions, ensembles, etc.) performance (up to 15%) for time series forecasting
- Conducted data preprocessing and analysis, visualization
- Developed data visualization application and its new features
- Optimized programming code for faster execution
- Fixed application’s bugs, refactored programming code
- Enhanced decision-making process through hypothesis testing
Position: Data Scientist/ Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent


*Currentl, I work for an Research and Development company in oil&gas sector as a junior researcher/data scientist. I have gained valuable experience in data science and analytics by working on various projects. One of the most exciting projects involved the use of the Random Forest algorithm to detect anomalies in oil production in real-time. I was actively involved in the project, helping with data preprocessing, model selection, and optimization. We were able to successfully detect anomalies in the data, and we are planning to publish a paper on our work. In another project, I worked on data analytics, where I was responsible for collecting data, performing feature engineering, and analyzing the data to obtain meaningful insights. Overall, my experience has helped me develop strong skills in data science and analytics.

* Besides, I had worked for one of the well-known energy companies in 2020 (in the geomechanics team) where I did data collection, in-depth data analysis, and linear regression model creation for them as a summer project. The study had helped them to solve their ongoing issue.
In my next role, I am looking for an opportunity to continue developing my skills in data science and analytics.  I would like to work in a collaborative and friendly environment where I can work with other talented individuals and learn from their experiences.One of the most important things I value for a company is to value innovation and encourage employees to take ownership of their work.
Position: Data Scientist/ Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: upper

I took second and third places at Olympiads in Mathematics, Physics, Programming, and Junior Academy of Sciences of Ukraine.
I have experience working with real data in the Student Council of the FICE Department at my University, as a Data Analyst and Scientist. I used to collect, process, and visualize Data from other students about events, new ideas, or graduates, and I had to make some data-driven decisions, recommendations, and analytics.
I want to apply my knowledge of Statistics, Artificial Intelligence, Machine Learning and Deep Learning in real projects