lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: upper

development and implementation of a machine learning model that increased the loan portfolio revenue by 20%
Design and implementation from scratch data lake for monitoring, reporting and modeling purposes. Automation of reporting and monitoring of key business performance indicators using cloud-based visual analytics tool. Development and implementation of score models which helped to reduce manual work and improved revenue. Integration of alternative external data sources for more accurate business management and orchestration strategy to optimize cost. Development and implementation NLP model for quality control.
try my hand at a new project, friendly team, favorable working conditions
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper


Design and implementation of regression models in vendor-managed inventory system.

Development of facial recognition system at the edge.

Management/Python scripting of AWS services related to Machine Learning and IoT.

Academic research. Teaching assistance.
Challenging problems, career development, stability.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: upper


Develop application using classification, segmentation, regression & GAN methods. Work with Keras, PyTorch, openCV and gradient boosting libraries.
Work interesting project in deep learning or image processing area.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent

I am quite good at handling data and converting it into something valuable :)
· Developed an app based on a neural network model that
detects and replaces ads in videos
· Redeveloped existing surface detection algorithm which
demonstrated an increase in accuracy
· Researched and successfully implemented algorithms for ads
detection and segmentation using OpenCV operations
· Took part in the development of an auto pilot for agriculture
robot, integrated our algorithms into the CARLA simulator,
implemented acquiring and processing data from sensors
· Was responsible for managing data annotators team, as well
as for data collection and preparation process
· Automated data mining processes which significantly
decreased the time required to collect and preprocess data
· Implemented web scraping techniques to extract and
organize competitor data
· Suggested and implemented predictive machine learning
algorithm to forecast company sales of new products
· Utilized data science libraries to structure and visualize data
Interesting and challenging projects
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent


Developed and deployed machine learning and natural language processing models. Built and fine-tuned a sentence similarity model and implemented a recommender system. Conducted data analyses and created visualizations to aid in understanding data and guide decision-making. Utilized tools such as Streamlit, Flask, and FastAPI to develop and deploy services. Experience working with cloud platforms such as AWS, and GCP. Worked with SQL and NoSQL databases, such as MySQL, PostgreSQL, and MongoDB. Designed and implemented web applications using Django and Flask, leveraging Docker and Docker Compose for containerization and Celery for task scheduling. Developed and implemented computer vision algorithms for video analytics projects Built and maintained a large-scale video processing pipeline using Python and Docker.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: intermediate

- Completed projects from PoC to production with reliable results
- Researched and made prototypes for techniques and algorithms for efficient solving of Landcover classification problem
- Designed and implemented efficient solutions on image segmentation (clouds and shadows detection)
- Strong mathematical background (completed master's degree on applied mathematics, PhD student)
- Developed and researched for cutting-edge projects concerning satellite imagery processing and data analysis. Participated in full cycle projects from PoC to production with reliable results on both well-defined and open-ended practical problems. (Data preprocessing, Neural network architecture design and implementation, Calibrating model and parameters based on results analysis, Developed production-ready code, Setup and ran in Docker via Airflow)

- Statistical analysis of probability distribution of stochastic variables, including confidence intervals estimation, check of uniformity, independence and other types of hypothesis building and validation

- Statistical analysis for corporate attendance bot: average lateness and working time, schedule and attendance visualization, personalized attendance prediction based on regression analysis results

- Text mining using statistical pattern learning (Zipf’s law, Heaps’ law, tf–idf) with further visualization and semantic network building
Ready to work hard and wisely on demanding projects, preferably related to Computer Vision. 
Not a Data Engineer. Don't prefer gambling industry projects. 
Expecting sane level of schedule flexibly.
Position: Data Scientist
Category: Python
Experience: 2 years | English: upper


Developed an ML model based on bakery product sales over the past couple of years (sales data from MsSQL DB), creating a forecast in the context of the day of the week. With further recalculation of the maximum production load among working hours from 8 am to 8 pm. The project used such libraries for data science as pandas, numpy (for filtering) statsmodels, sklearn, pmdarima (modeling): in addition, a docker container was configured that served as a connector between the MsSQL DB and the model itself. The data was downloaded, filtered and cleaned of outliers, a forecast was made for each specific shod_id and product_id and then uploaded to the MsSQl DB
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


Developed an ML model for car accident prediction using historical data, contributing to improved risk assessment and safety measures in the automotive sector.
Performed extensive data processing, including data cleaning and feature engineering, to ensure high-quality datasets for accurate modeling.
Conducted data management tasks, ensuring efficient storage, retrieval, and organization of data for various projects.
Automated the generation of six reports, streamlining data analysis and reporting processes for enhanced efficiency.
Conducted in-depth analysis of customers and driver behavior, providing valuable insights for strategic decision-making and business growth.
Collaborated with cross-functional teams to gather requirements and integrate data science solutions into various business processes.
Leveraged Python scripting, SQL, and R to perform advanced data analytics and derive actionable insights.
Utilized visualization tools like Tableau and Power BI to create compelling visual representations of data and facilitate data-driven storytelling.
Worked on various data science projects, contributing to a deeper understanding of business challenges and opportunities.
Integrated web scraping for real-time data enrichment
Position: Data Scientist
Category: Data Science
Experience: 6 years | English: fluent


•	Developed a scraping program to get data from a local website using selenium.
•	Created a food recipe website using HTML, CSS, JavaScript as my frontend technologies and Python and fastAPI as my backend. I integrated mongoDB as my database.
•	Collaborated with a partner to create a simple shell program for Linux using C

Looking to improve in my areas of interest, particularly in C and Python
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: upper

In addition to the the achievements stated in Work Experience section, I: 
- Was one of 12 top-performing students from Kyivstar Big Data Schools (acceptance rate 2%) who was hired to Kyivstar;
- Started to analyse time series at first place of work and tried to implement ideas to production;
- Participated in Kaggle competitions;
- Graduated at Mechanics and Mathematics department, Taras Shevchenko National University of Kyiv;
- Finished Coursera and Yandex ML courses (Math and Python for data analysis; Learning on marked data; Search of patterns in data; Сonstruct conclusions on the data).
Developed recommendation system (RS) for media portal (compared different algs with A/B, bandito testing). Tools used: 
- popular libraries lightFM, ALS;
- user2user, item2item.

Used time series analysis to: 
-  predict future business metrics. (SARIMA, XGBoost, Neural Networks, Prophet); 
- predict future workload for warehouse.

Used heat maps (on R) based on telecom data with the following data filters:
- daily migration in Kyiv;
- work migration in Kyiv region.

Built predictive models to:
- conduct SMS campaigns, targeted on specific users; 
- predict article's position in Google search results;
- predict growing and declining businesses.

Other analytical tasks:
- identified key features for top articles in Google search;
- detected anomalies in articles.

Computer Vision:
- identified users' favourite colours based on their clothes on photos (used YOLO3 neural network).

NLP:
- used TF-IDF, Bert to find similar articles.

Research:
- compared different text-to-speech services (AWS, Azure, IBM, Yandex, Google), to make "podcast like" news. 
- compared photo object detection services (Google, AWS, Azure).

Project Management: 
- prepared Data Science roadmap, with all possible and impossible DS improvements for our product to further discuss with management what we can do next;
- initiated retrospective session to improve team work.
- Want to make impact on business decisions;
- Would be an advantage if project was focused on social issues or environmental problems;
- Opportunity to improve public speaking skills and participate in conferences/other public events;
- Opportunity to work remotely.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: upper

- Development of the Methodology for validation of credit risk models and providing validation of PD & LGD credit risk models for the bank (TOP-5) from scratch (it was a unique project in Ukraine);
- Implementation of the Methodology of the probability of default under IFRS 9 and participation in the development and implementation of internal Methodology of impairment for leading Ukrainian bank (2017 year, unique project of implementation of under IFRS 9 in Ukraine);
- Development of statistical models (Regression, Classification, Scoring, Time-series forecasting, PIT and TTC credit risk models) in R for Ukrainian banks;
- Leading small projects;
- The ability to work under pressure and limited deadlines, providing a self-development at the same time.
•	Developed statistical models (Regression, Classification, Scoring, Time-series forecasting, PIT and TTC credit risk models) in Excel and R for Ukrainian banks;
•	Provided data cleansing and quality assessment as part of model development;
•	Implemented the Methodology of the probability of default under IFRS 9 for leading Ukrainian bank;
•	Took part in the development and implementation of internal Methodology of impairment for leading Ukrainian bank;
•	Took part in the development of the Methodology for validation of credit risk models for the bank (TOP-5);
•	Provided a validation of PD & LGD credit risk models under IFRS 9 for the bank (TOP-5);
•	Participated in the projects of development of methodologies and credit risk models under IFRS 9 for CIS bank;
•	Took part in the preparation of software requirements specification for banking software system;
•	Provided the design of financial reports, presentations and preparing statements;
•	Created the procedure of calculation of PD, LGD, and probability of repayment scenarios as a part of the process of impairment assessment for leading Ukrainian bank;
•	Took part in the process of renovation of the credit process and creation of the credit procedure for leading Ukrainian bank;
•	Took part in the process of development of the internal rating (scoring) model for leading Ukrainian bank. Supported and updated it;
•	Provided explicit financial statement analysis and prepared risk estimates on Ukrainian banks;
•	Performed a comprehensive analysis of insolvent banks and the reasons for their bankruptcy;
•	Led small projects (1-2 people) and project modules within larger projects for clients;
•	Led, advised and trained junior staff on and off projects;
•	Developed the service propositions, supported the proposal activities, managed relationship and interaction with counterparties at the client site;

Skills:
•	Practical (good) skills in R, SQL Server, MS Access, JIRA;
•	Experience with Statistica, Python, JAVA, HTML, XML.
- Opportunity for self-development in modeling and ML;
- Opportunity to lead small projects or project modules within larger projects for clients;
- Nice to be - to use deep knowledge in finance.
Position: Data Scientist
Category: Java
Experience: 2 years | English: fluent


Developed the first credit scoring model in CIS region as a part of PASHA Bank's Digital SME project. Collected and processed data, tested multiple classification algorithms, and prepared financial impact based on the predictions. Currently working on ML-based limit policy module within the same project.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: upper

- Developing high load online services using the state-of-the-art solutions from zero to production

- Gold medal, top 1% on Kaggle Recursion Cellular Image Classification
- Developing production system for high load online Neural Machine Translation system using the latest architecture based on self-attention.
 - Developing an interactive NMT system, word alignment system, document alignment system, glossary extraction system, morphology services
 - Deploying services
 - Data mining, cleaning, processing
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


- Development and maintaining voice recognition modelss(training Neural Networks)
- Writing automation scripts (Python, Bash)
- Fixing defects in voice recognition models (regex, data analysis)
- Writing a software for electronic devices using GNU Octave. Applications, which I was developing are being used for operating and calibration of devices. I was also applying the machine learning techniques while developing of the software.
Position: Data Scientist
Category: Data Science
Experience: 7 years | English: fluent


Development and maintenance of statistical and econometric models for banks and other financial institutions;
Credit risk modeling / regulatory models / IFRS 9 implementation;
Implementation of models on IT infrastructure;
Performing user acceptance test (UAT);
Model documentation.

I worked for multiple international organizations in Azerbaijan, Poland and the Netherlands. Currently, I am based in Amsterdam.
Position: Data Scientist
Category: Data Science
Experience: 7 years | English: intermediate


Development and support of autonomous navigation systems for drones using ROS,
OpenCV, PCL, MRPT;
Development and modernization of SLAM algorithms;
Development recognition and objects classification systems using Tensorflow,
Torch, Cafe;
Development of embedded computer vision systems based on the Yocto-project;
Creation and modification of neural networks for computer vision based on NCC,
Darknet, ResNet, SSD, MobileNet and others;
Developing motion planners using OMPL.
Experienced in implementation of edge cutting scientific development:
GA-Net: Guided Aggregation Net for End-To-End Stereo Matching,
Real-Time Self-Adaptive Deep Stereo,
Video Action Transformer Network
Relational Action Forecasting,
Long-Term Feature Banks for Detailed Video Understanding
A Multitask Learning Approach to Action Quality Assessment,
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation,
TopNet: Structural Point Cloud Decoder,
FlowNet3D: Learning Scene Flow in 3D Point Clouds,
SSN: Learning Sparse Switchable Normalization via SparsestMax,
DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous
Driving Scenarios,
Pose2Seg: Detection Free Human Instance Segmentation,
GA-Net: Guided Aggregation Net for End-To-End Stereo Matching.
BAD SLAM: Bundle Adjusted Direct RGB-D SLAM,
An Efficient Schmidt-EKF for 3D Visual-Inertial SLAM.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: upper

Participated in the development of several software packages for data processing, pattern recognition and simulation of results in high energy physics experiments.
Development of visualization tools, user interfaces and deployment features (like API endpoints).
Development and deployment of complex deep learning solutions for predicting of the outcomes of sports competitions and the price movement trajectories of various financial instruments.
Development of machine learning and deep learning models for classification and prediction, creation of user interfaces, deployment and visualization of results.
Development of the server side of web applications, bots for social networks and trading robots.
Web projects: online casinos, cryptocurrency exchanges, financial market brokers, online stores
Interested in professional growth on projects related to machine learning and artificial intelligence.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: intermediate


Development of Transformer models. Mapping and motion simulation. Building predictive neural networks, comparative analysis, models evaluation and tuning. Developing algorithms for points projection and affine transformation. Object Tracking, Object Detection, Segmentation, XGBoost, Demand Forecasting.
Neural Networks - pytorch, tensorflow, keras
Data Processing - numpy, pandas, BigQuery, R
Orchistration tools - Mlflow, Airflow
Clouds - AWS, GCP
Position: Data Scientist
Category: Python
Experience: 1.5 years | English: upper


DevOps engineer experienced in optimizing systems and workflows. Implemented CI/CD pipelines, Kubernetes, Docker. Coded in Python, Java, Fluentd. Focus on automation and data-driven optimization. Created computer vision model for hand gesture recognition. Developed virtual steering wheel using OpenCV and PyAutoGUI. Published demo video showcasing interactive system.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper

Education:
    Bachelors degree in engineering sphere (VNTU)
Certifications:
 - Mathematics for Machine Learning Specialization by Imperial College London
 - Machine Learning by Stanford University
  - Deep Learning Specialization by DeepLearning.AI
Diabetic Retinopathy (computer vision)
Main responsibility: 
 - Data collection.
 - Data Preparation and Feature Engineering.
 - Model creation and training (classification and segmentation problem).
 - MLOps on AWS with automated training and deploying pipeline with AWS tools (CLI, Sagemaker, S3, API Gateway).

Floor Inserting (computer vision)
Main responsibility:
 - Data collection.
 - Data Preparation and Feature Engineering.
 - Train segmentation model for floor detection (fine tuning Hugging face model).
 - Create python scripts for floor changing.
 - Create REST API.
 - Deploying API on AWS (Lambda, API Gateway).
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate

• KPI Upgrade hackathon winner team leader with KPI Eye app — CV-based web app for virtual excursions. Currently in development.
• 2022 and 2023 INT20H hackathon finalist in the Data Science section.
• Day F hackathon 3rd place with a time scheduling app. Team leader and the author of the main algorithm (using ML).
• IASA Data Science Champ main organizer.
• Has won the IT Olympiad of Ukraine three times, among thousands of participants nationwide.
Diploma on the decision support system for lymphoma diagnosis. I have created a medical system for the classification of lymphoma full-scale images (hundred thousand pixels wide) and for the search for similar images. I used and modified existing algorithms and created a web system.
Position: Data Scientist
Category: Python
Experience: 5 years | English: upper

Solid knowledge in Classical Computer Vision. 
Unfinished PhD in Applied math (FEM)
Domain: Energy & Manufacturing, Oil & Gas, Fossil fuels.

Responsibilities: Discover clients needs & requirements, research feasible solutions, organize & lead DS team, understand & preprocess data, develop & deliver complete solution to the client. loop ;)

Tools & Techs: Python, pandas, sql, tensorflow/keras, OpenCV, Cloud AWS/GCP.
Ideally but not necessary I would like to switch back from TimeSeries/Tabular data to Computer Vision problems.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate

Machine Learning Coursera
Specialization contained 3 courses
1) Supervised Machine Learning: Regression and Classification
2) Advanced Learning Algorithms 
3) Unsupervised Learning, Recommenders, Reinforcement Learning


Develop your career with Google Cloud: ML and data Course 
On this course, skills were acquired in interacting with Google Cloud and its various products for project management, data storage and analysis, as well as building machine learning models and utilizing various APIs for it. 

Google Cloud certification "Cloud Digital Leader"
A successful candidate can articulate the capabilities of Google Cloud core products and services and how they benefit organizations. The candidate can also describe common business use cases and how cloud solutions support an enterprise.
Don`t have work experience.  
I recently graduated from the National Technical University of Ukraine "Kyiv Polytechnic Institute" (NTUU "KPI") with a bachelor's degree in Cybersecurity. In my bachelor thesis "Anomaly detection in RDP authentication logs" I applied machine learning to cybersecurity problems. 
At the same time, I have been developing my skills in Data Science with courses (kaggle, coursera, etc, datacamp), reading articles and watching videos about data science. Now I am starting to pursue my master's degree in Data Science, where i want to get deep understanding of modern technologies and solutions in DS.
kaggle: /andriikolesnyk
Ready for everything!
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper

Graduated from UPML KNU.
Prizewinner of regional Olympiads in mathematics (III diploma), chemistry (3 II diplomas), a participant in the All-Ukrainian Olympiad in chemistry.
I took part in programming Olympiads (ACM, school, Google contest).
DRCT
Creating dashboards (Google Data Studio)
Working with SQL (Big Query)
ML models for analysis 

Vero cash
July 2021- September 2021
- Pandas, Numpy
- Writing documentation
- Reports creating
- Excel

LetyShops, Kyiv (practice)
February 2020 - March 2020
- Data analysis
- Data visualisation (data studio)
- Self-presentation (project)