lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: fluent

- As a data analyst and domain expert, played major role in evaluation/assessment of text classification models during its' creation and improvement. Collaborated with the team of developers, communicated findings and insights through visualizations & reports in order to show system drawbacks and improvements once fixed. Technologies: python, matplotlib, seaborn, bokeh, pandas, numpy, etc.
- As an engineer, created a micro-service system which process data from main pipeline using spark, than crawling hundred of thousands domains in order to enrich and improve processing in the main pipeline. Technologies: Docker, Kubernetes, Python, BeautifulSoup, Selenium, Scala, Apache Spark (in total 3 different subsystems).
- As a domain expert and engineer, significantly improved and refactored pivotal piece of data pipeline for search extraction. Technologies: Scala, Spark.
- As a data scientist, crunched sales prediction problem for a major FMCG company (time series forecasting). Technologies: python, pytest, pandas, LightGBM, FB Prophet
- Multiple times hackathons winner
Full-cycle ML product development from problem definition and gathering requirements to deployment in production systems. 
I worked on both, ML and non-ML based solutions to solve business problems. 

ML competencies:
- text classification 
- time-series forecasting
- data preparation
- feature engineering
- model evaluation

I'm interested in deep learning based approaches in NLP or CV, including deployment (serving) of DL models.
- Not a data engineer, DevOps, BI, Scala developer positions
- Not interested in gambling, porn, banking, adtech industries
- Prefer product-oriented company, not "service"/outsource/"boutique" company, please
- Preferably mid-size product company (~50-500 people)
- Flexible environment with collaboration style rather than micro-management
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: intermediate

Awards:
One of the top 3 students at Kyivstar Big Data School 5.0, 2020

Certifications:
Convolutional Neural Networks - Coursera, 2021
Structuring Machine Learning Projects - Coursera, 2021
Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization - Coursera, 2021
Neural Networks and Deep Learning - Coursera, 2021
Big Data School 5.0 - Kyivstar, 2020
Supervised Learning - Coursera, 2020
Dive into Python - Coursera, 2020
I am a motivated student with a strong math background and 1+ years of experience using data analysis and machine learning. I know how to solve supervised and unsupervised learning problems, object detection, image and text classification, image segmentation, face recognition, and neural style transfer. Now, I am working on predicting COVID-19 using a chest X-ray. I will be glad to share with you my result.
I am looking for a job to realize my potential by performing complex and non-standard tasks for the result.
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 1.5 years | English: upper


I have 2 years of commercial experience in Data Science(NLP) with researching and
developing NLP solutions for e-commerce needs and additionally 1 year of pet-projects
creation.
I am a specialist in the field of computerization and system analyst with knowledge of Python,
SQL, OOP principles with hands-on experience in both machine learning and deep learning,
including supervised, unsupervised, semi-supervised and reinforcement learning.
I have strong analytical skills, easy and fast learning ability.

Tasks types on which I worked:
 Text generation
 Topic Detection
 Structures and Entities extraction
 Sentiment Analysis
 Clustering, Classification
 Community detection
 Feature selection, Dimensionality reduction
 Data consistency analysis
I expect to continue using NLP approaches in e-commerce domain. Also, ready to consider other options my skills utilizing.
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 2.5 years | English: upper


I have experience working as a machine learning engineer for year and a year of experience working as a data analyst.
As a machine learning engineer, my key responsibilities were:
-speed prediction and expeditors ranking for a logistic project
-data scrapping
-EDA
-time series forecasting
-develop core components for platform related to machine learning

As a data analyst, I worked a lot with the marketing team giving them results of their current marketing campaigns and insights for their future work.
My main tasks were:
-reports automation process;
-marketing automation(Google API).

I also have traineeship in It-Jim company as a Computer Vision engineer for a month, working on a 3D Object Segmentation task. 

Now I am interested in computer vision and have a deep understanding of classical cv and the deep learning side. I want to explore SOTA in the field of computer vision.
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: fluent

The project I enjoyed the most was the Soil Erosion, which is the great solution for automated soil degradation detection. Also I enjoyed building recommendation system for my Telegram bot (so called pet-project), though not so much deploying it.
Most of my experience is in data science and machine learning. I worked on various languages and projects some of which are available on the GitHub. As of now I have occupied Data Science position in three companies and am still a part of Machine Learning team.
I hope to learn even more than I know now and benefit humanity. I wish I could do more signal processing and conseqent ML projects even though I am not that experienced in it.
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent

Co-author of 20+ published papers in high-impact journals and several book chapters on optics.
PhD (Physics), University of Queensland, Australia.
Python: 2 years
Developed an algorithm for on-line sub-pixel detection of particles in microscopy images (Tensorflow /Keras/ OpenCV, NumPy).
Change detection in a noisy time-series signal (NumPy, OpenCV).
Created a protocol storage and calculation system for buffer solution preparation (non-commercial, SQLite, TKinter).
Snippets for excel data processing and conversion (Pandas, NumPy, Tkinter)
Data visualization (matplolib, seaborn)

MATLAB: 10 years. Data analysis and visualization, analog signal processing, image acquisition and processing.
A pipeline for cell image segmentation and protein tracking. 
Data visualization

LabVIEW: 7 years
Image processing and acquisition using CCD and CMOS cameras, camera synchronization with data acquisition systems, power spectrum analysis. 

Hardware experience:
Custom-built several optical microscopes, hands-on experience with optical detectors, data acquisition software, FPGA programming.

Other experience: 
UI development for online magazine (ActionScript 3, commercial)
Freelance: several small projects on data analysis (OCR, signal processing)
I have a strong mathematical background (statistics, tensor and vector analysis, linear algebra) and passion for ML/AI systems. Given my broad experience in image analysis and signal processing, a project in Computer Vision or image processing/generation would be a good fit for both parties. However, I would be happy to consider any interesting proposals related to data science and machine learning.
Position: Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: fluent

Opening new areas & building teams from scratch in several companies
Strong mathematical background.
10+ years in project/product/team management
6 years in software development
3 years in ML (pandas, numpy, scikit-learn, TensorFlow)
1 year head of ML team
Looking for a new challenge, preferably in the field of data analysis projects/products with machine learning.
Position: Data Scientist | Machine Learning Engineer | Big Data Engineer
Category: Data Science
Experience: 5 years | English: upper

As a diploma project made research in "Automated architecture search of deep neural networks for image classification". Model based on searching CNN architectures within a continuous domain using gradient descent (solving bilevel optimization problem).
I have a Master's degree in Data Analytics. In Data Science for 4+ years. Before worked as a python developer (2 years) and Game developer (developed augmented reality games in Snapchat for 2 years).

Past projects:
- Building databricks workflows for big data to find car signal anomalies. Transform and organize big data from data lake. Build ml pipelines to find anomalies. (Spark, Databricks, mlflow, XGBoost)
- Video recommendation service. 
Developed pipeline on Apache Airflow with the switcher of models: deep recommender and two-step model. (user-content based models), A/B testing
- Service to tag invoices (NLP) 
Build AWS Sagemaker pipeline with different models (classification, week-supervision). 
     Also, I led the team and worked directly with the client on an experimental stream doing various things: PU learning, Multiple-Instance learning, Anomaly Detection, extract not biased subsamples
- Demand forecast for suppliers to optimize logistics.
Developed a flexible pipeline that is able to be trained on different data for different markets and countries. Optimize warehouses logistics (Databricks, Spark)
- Service to recommend an optimal price for hotel rooms to maximize income (time-series)
There was a lot of work customizing architecture for the encoder-decoder model, preventing leaked features (monotonic constraint), and finally extracting the desired features dependence. 
- Predict returning of the customer (Big data, Big query)
- Service for lungs diagnosis. (Computer vision)
The service segment lungs, and is available to detect 10+ diseases, and segment pneumothorax
- Anomaly detection service for scraping company (Semi-supervised)
Complex feature engineering work. (fighting with aggregated-correlated features)
- Service to predict policy price using minimal input data for insurance companies. 
Besides standard work with the model and service, there was done analysis on feature importance, using SHAP and own techniques.
I am currently located in Europe.
Position: Data Scientist / Machine Learning Engineer / Computer Vision
Category: Data Science
Experience: 5 years | English: fluent

-Improved accuracy of eye tracking system by developing a new solution for one of the parts of the whole system.

-Developed a system which measures user's attention based on data from a webcam.

-During my time at school and university I have won various mathematical competitions on all levels (regional, national and international).

-Academic IELTS 8.0
2018-2019
-Implemented a simulation procedure for interest rate curves under Heath-Jarrow-Morton framework
-Implemented Cost of Capital based approach for
pricing longevity-linked securities 

2019-2022
Machine Learning Engineer-Researcher and Data Scientist. Worked on:
-Improving a webcam based eye-tracking system
-Developing an emotion recognition system
-Developing an attention measuring system
-Designing and implementing statistical tests for reaction time testing and MaxDiff analysis

2020-2023 (part-time)
Lecturer at Taras Shevchenko National University of Kyiv teaching following subjects:
-Machine Learning
-Computer Vision
-Deep Learning

Skills:
-Machine and Deep Learning (regression, classification, GANs, CNNs, segmentation, PCA)
-Computer Vision (image processing, 3D pose estimation)
-Statistics (hypothesis testing, parameter estimation, Monte-Carlo, stochastic processes)
-Mathematics (calculus, probability theory, linear algebra, geometry, optimization)
-Financial/Actuarial mathematics
I would like to work in a product company either in Computer Vision or Data Science domain.
Position: Data Scientist, Machine Learning Engineer, Computer Vision Engineer, R&D Engineer
Category: Data Science
Experience: 2.5 years | English: fluent

Multiple winner of numerous hackathons, self-learner with great desire to figure out stuff. And so on. Does it even matter? Just check my skills.
Worked on Computer Vision System for Augmented Reality project. Worked on detection, segmentation and recognition
problems, as well as on client-server system, firstly based on REST API, but then swithed to TCP/IP. Used
tensorflow/opencv/numpy/keras stack.

Worked on Computer Vision system for drones. Worked on segmentation, detection and distance estimation problems.
Used tensorflow/opencv/pytorch/numpy/ROS/Linux software stack and Intel RealSence/Intel Nuke hardware stack.

Worked as outsource Data Scientist on different client projects. Worked on high variety of Computer Vision and Natural
Language Processing tasks. Used pytorch/tensorflow/numpy/opencv/AWS/Microsoft Azure stack.

Worked as temporary AI developer for the gamedev project.
Competitive salary, friendly team
Position: Data Scientist / Machine Learning Engineer / Data Analyst
Category: Data Science
Experience: 0.5 years | English: fluent

- Junior Member of The New York Academy of Sciences. Worked on monitoring and prevention of the Eutrophication process using Machine Learning

- Ukrainian National Scientific Research Competition in Micro- and Macroeconomics, Silver Medal Winner

- International Youth Math Challenge, Silver Honour winner

- Oblast stage of the Computer Science Olympiad (C++, algorithms), Silver Medal
Revenue Grid, Software Engineering Intern:
-  Automated Salesforce CRM processes and created signals that guided sales teams of the company’s customers
- Synchronized users’ Google and Microsoft services data with CRM using Microsoft Azure Logic Apps and SAQL

New York Academy of Sciences:
- Worked on monitoring and prevention of the Eutrophication process using Machine Learning (specifically CNN)

Mobile Developer at the nonprofit startup:
 - Worked on the application front-end using Flutter
Position: Data Scientist / Machine Learning Engineer/ Data Analyst
Category: Data Science
Experience: 1 years | English: intermediate


Work Experience:
- ML (1year):
Data science and machine learning practical within 1 year experience in Fintech.  Development and implementation of Loan Defaults Predictive Models and Collection Scoring Models (CatBoost, LogisticRegression). 
Experienced in ML project life cycle:
data collection, preprocessing, feature engineering, training, validation and testing, post-deployment monitoring.
Customer segmentation and development of effective communication strategies by marketing and collection departments for each group.

- PHP developer (2 years):
Development of functionality for a website. Working in a team according to the principles of Scrum methodology. Yii framework, MySQL, Memcached

- Economic Analyst (more than 5 years):
Management accounting, calculation of economic indicators. Analysis of economic activity.

Education:
Economic informatics and statistics (master's degree, Oles Honchar Dnipro National University)
The Data Science Course 2021: Complete Data Science Bootcamp (Udemy)
PowerBI (Udemy) and BABOK
Position: Data Scientist, Machine Learning Engineer, Data Analyst
Category: Data Science
Experience: 0 years | English: fluent

Bachelor thesis on authorship attribution from analysis of anonymous texts in social networks and dating apps. It involved machine learning and a lot of preprocessing. Term papers involved SQL, Python and C. Knowledge of math (statistics, calculus, linear algebra etc.)
No working experience as a software engineer or data scientist outside university program and self-education. Some experience as a project manager, also worked as a translator.
I have a pet project - Android app written in Kotlin with multiple variants and implementations. It is periodically updated on Github and used by me and my friends.
Fields not related or very remotely related to data science or at least Python.
Position: Data Scientist/Machine Learning Engineer/Data Analyst
Category: Data Science
Experience: 5 years | English: upper


In May 2019, I joined the Operations team at Bolt Technologies, a European mobility company that was planning to launch a ride-hailing app in my home country of Kazakhstan. Within just four months, our team of five people successfully facilitated the most successful launch for our company present in 35 countries at that time. In the very first week, we managed to hit the 100k rides mark.

During my time at Bolt Technologies, I was responsible for various operational duties, including analyzing data and making decisions based on the findings. It was then that I first encountered programming and was encouraged by my superiors to start learning a programming language. I have since enrolled in several programming classes with the goal of entering the field of Data Science. I have been studying relevant skills for several months and feel that now is a good time for me to start pursuing my first job in this field.
I am looking to kick-off my career in Data Science or Machine Learning fields.
Position: Data Scientist/Machine Learning Engineer/Data Analyst
Category: Data Science
Experience: 2 years | English: upper

2nd place at the All-Ukrainian competition of student research papers in the specialty ”Computer Science”.
Scholarship of the President of Ukraine.
Young Scientist Award for the Best Research Paper.
Master's Degree in Computer Science. Right now studying as a Ph.D. student at Igor Sikorsky Kyiv Polytechnic Institute. 
In university, I participated in several research projects related to Data Science in Biomedicine and Healthcare. For example, we made the decision support system for liver diagnostics via medical ultrasound images, where I created the ML model by constructing my own algorithm (with principles of Decision Tree, Random Forest, and Group Method of Data Handling). This system was implemented in the Institute of Nuclear Medicine and Diagnostic Radiology.
I worked for 1.5 years as Data Analyst, where my main responsibility was to create analytical reports by using SQL queries and/or Python scripts. In some projects, I could use DS approaches to create ML solutions like forecasting, logo recognition, audio recognition, etc.
Right now, I'm looking for working on real DS/ML projects, where I can fully concentrate on making hypotheses and models. Also, I won't be squeamish about working as a Data Analyst
You can check more details of my background in the CV.
I hope that the skills I have acquired will help me get a decent job and be of invaluable benefit to the company.
Position: Data Scientist, Machine Learning Engineer, Deep Learning Engineer, Computer Vision Engineer, NLP Engineer, Data Analyst
Category: Data Science
Experience: 2 years | English: fluent

I have finished Bachelor of Sciences in Computer Science in ADA University, Baku, Azerbaijan with an exchange semester of education in Kadir Has University, Istanbul, Turkey. I have also studied Master of Data Science and Artificial Intelligence in French-Azerbaijani University and University of Strasbourg which is a dual master program. I have accomplished scholarship rewards in my bachelor and master degrees and many certificates from online learning platforms such as Coursera and Udemy related to Data Science, Artificial Intelligence, Statistics and Probability, Python, SQL, Machine Learning, Deep Learning, Image Analysis and Processing, Computer Vision, Natural Language Processing (NLP) and many more fields on AI.
I have 4 years of experience in Python and SQL, 3.5 years of experience in Data Science, Machine Learning, Deep Learning, and Artificial İntelligence fields. Additionally, I have work experience of mentoring, teaching, and dealing with real world applications in the fields mentioned above in QSS Analytics and Data Science Academy. As a Data Science intern in QSS Analytics, Baku, Azerbaijan my responsibilities were to manage official Social Media accounts such as Facebook and LinkedIn and to improve Python, Machine Learning and SQL skills. In Data Science Academy, my work was to improve students' Data Science skills related to Python and Machine learning by teaching them individually and in a class, and preparing slides, codes, and tasks for the lectures at Data Science Bootcamp program. Also, I have been a Computer Vision İntern at Uqudo, Dubai, UAE (remote) from January, 2023 till June 2023.  From July 2022 till June 2023, I have worked as Jr. Data Scientist at Yelo Bank, Baku, Azerbaijan. Currently, I continue my career as Middle Data Scientist in Yelo Bank. Here, my responsibilities include building risk engines (scoring) for online loan applications designed for retail, micro, and agricultural businesses, building models for customers' lifetime value, monitoring and supporting engines and models by analyzing them in production, and preparing reports of engines and models. More information about my projects, certifications, and other qualifications can be found on my LinkedIn account whose link is available on my CV.
My expectations include proper jobs or projects to help companies and to gain more experience, and get suitable salary.
Position: Data Scientist / Machine Learning Engineer (Middle, preferably Computer Vision)
Category: Data Science
Experience: 3 years | English: upper


I have vast experience in a wide range of computer vision tasks (object detection and tracking, segmentation, classification) using classic computer vision algorithms and deep learning. A large part of my work included video and photo processing (video streams, video capture, frame analysis, camera calibration), face processing (face detection, facial landmarks, blink detection, head pose estimation, gaze estimation in 2D and 3D setup).
Side projects: template matching, person re-identification, face-antispoofing/liveness detection, 3D mesh denoising.

As a part of a startup research team, I was responsible for the analysis and implication of the SOTA approaches, faced different technologies, especially web application development processes, and had an opportunity to get experience in different tech roles. The main challenge was to create CV models that would have a plausible result on a limited resource (client-side computation).
Main tools:
- OpenCV, Dlib, OpenVINO
- DL libraries (Tensorflow, Pytorch)
- Numpy, Pandas
- Visualization tools
- Flask, Scrapy, Docker, docker-compose
Programming language: Python, also familiar with: C/C++, Rust, JavaScript, R
I would like to be responsible for tasks mainly related to the Computer Vision field but a small portion of tasks related to DS areas would be fine. 
My top priority is a company that seeks a team player for a solid team and projects NOT connected to gambling/bidding/gaming/advertising.  
It is important for me to have an opportunity for remote working mode and a flexible schedule
Position: Data Scientist, Machine Learning Engineer, MLOps
Category: Data Science
Experience: 3 years | English: fluent

-Top 9.49% in Leetcode. Username: KONAKONA666
-Participated in National Olympiad in Informatics, Kazakhstan passed the qualifying rounds from school round to nationwide.
-Decathlon Hackathon Winner, 2018
-HackNU 2021 Microsoft track 3rd place.
-Delivered information extraction from utility bills and bank statements. Developed an information extraction system to handle arbitrary layouts. Stack: easyOCR, flairNLP, PyTorch, AWS SageMaker.
-Designed and implemented a custom model combining triplet loss and glove concepts in PyTorch to handle hierarchical
dependency. Analyzed sales data using product embeddings and improved f1 metrics in a downstream task by 10%.
-Add a feature that is used by more than 30k employees using xAI, SHAPvalues, PyTorch, XGBoost, CatBoost.
-Set up CI/CD using Github Actions for ML Team, pylint, mypy. MLOps and collaborated with different teams to deploy ML models. Kubeflow, MLFlow.
-Created tools that are used by 15+ other developers and made testing easier.