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


As an experienced Machine Learning Scientist with 10+ years in the IT sector and higher education, I excel in research and high-level development projects using ML models. Skilled in dimension reduction, feature extraction, and data manipulation with Python. Developed ML models for real-life data (parametric and non-parametric) like K-means clustering and XGBoost. Proficient in Deep Learning and NLP with transformer models for complex problem-solving. Experienced in setting up end-to-end pipelines on Docker and AWS. Strong programming skills in low-level/high-level languages and scripting. Thrive in diverse international teams, leading agile (scrum) and managing large groups.

Projects:
- NLP for Amharic: Improved accuracy from 62% to 92% using Logistic Regression, SVM, and XGBoost.
- Clone detection on coding data: Led NLP project with CodeBERT, UniXcoder, and Doc2Vec for accurate results.
- Price prediction on trading data: Used Linear, Ridge, Lasso Regression, AdaBoost, XGBoost for trend prediction. Utilized Pandas, Numpy, Matplotlib, Seaborn.
- EDA on heart stroke data: Analyzed multivariate biological data using KNN, Logistic Regression, Pandas, Numpy, Seaborn, Yellowbrick.
- Microarray gene-expression analysis: Employed PCA, SVD for dimensionality reduction. Used feature selection, ANN, KNN, DT, RF, SVM. Improved cancer classification.

Completed 20+ ML, Deep Learning, NLP projects.

Looking to enhance skills in Data Engineering and Data Science Engineering. Goal is to design efficient data pipelines, manage large-scale infrastructure, and optimize data-driven solutions.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


As an Intern at Explore AI Academy, while working on a team, I analyzed a large dataset and created a visualization to identify areas where online learners need interventions. During this project, I queried data from a PostgreSQL database using Python in a Jupyter notebook connected to the Database and then created a dashboard using Microsoft Power BI to draw insights from learners’ progress on the learning platform.


I have also worked on a Natural Language Processing project where I trained a machine learning model to classify the sentiment of a tweet on climate change to an accuracy of 85.6%,  created a web application, and then deployed both on AWS EC2 Instance. While working on this team, I used Python extensively and collaborated using version control software and collaboration tools, git and GitHub.
I look forward to working on a team with growth mindset and less redundant tasks.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


As an MTech Data Analytics graduate with 2 years of experience in financial, sales, and customer analytics, as well as machine learning, I have honed my skills in working with cross-functional teams and delivering high-quality results. I believe my expertise and experience make me a strong fit for the position you are looking for.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper

Implemented max bid for models that reduced costs by 17%.
Created a limitation mechanism for RTB model.
Made Tableau report as a main source of tracking performance.
Created an automated system for monitoring Tableau reports. The system checks reports for several types of errors and send messages if there is an error.
I did refactoring and improvement of forecast project, architecture was made from the scratch and also new features were added.
As a part of the BigData team I'm working on real time bidding model that works with Native ads. I'm taking part in feature generation, supporting development with different analyses and creating Tableau reports for tracking KPI. I'm also helping product team with small tasks.

I worked on new projects such as scraping, performance forecasting, developing new data pipeline, etc. In addition to this I did analyses and supported Tableau reports. I also cared about PostgreSQL database that my team used during the work.

I developed databases and estimated credit risks. I worked with SQL Server and helped my colleagues preparing month and other reports in Excel.
A small team that is responsible for different areas and does diverse tasks.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: fluent

Optimized software for high-res multi-video streams using Deepstream.
Converted pipeline from Python to C++, enhancing capacity.
Designed complex systems via the multi-container Docker Compose app.
Accelerated deep learning models on A100 GPU devices by leveraging TensorRT optimization.
As a passionate AI engineer with over 3 years of experience in machine learning and data analysis, I've optimized Machine Learning pipelines and created a market analysis tool trusted by major marketing companies. I have a proven ability to successfully tackle new challenges and a passion for discovering and implementing innovative techniques to optimize product performance.
I constantly seek new challenges and thrive in dynamic environments where I can bring my skills and creativity to the forefront. I am not one to be satisfied with repetitive, mundane tasks and am always on the lookout for opportunities to push my limits and deliver exceptional results.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper


As a recent graduate with a passion for machine
learning, I am interested in kickstarting my
career in AI, the field, that truly inspires me.
In addition to my academic pursuits, I
completed online courses and certifications in
various ML frameworks and data manipulation
libraries like TensorFlow, Scikit-learn, and
Pandas. As well as immersing myself in projects
to gain an understanding of various algorithms
and techniques.
I am seeking a supportive environment where I
can learn from experienced professionals and
keep growing while contributing fresh
perspectives. I am hard-working, proactive and a
quick learner, constantly developing new skills
and abilities.
Position: Data Scientist
Category: Python
Experience: 4 years | English: fluent

ML Model Construction from Scratch
Advanced Biostatics Dashboard Creation using Power BI
Full Pipeline Automation using Rest API & Python
As a result-driven and motivated Data Scientist | Analyst with 4
years of experience, I am deeply committed to leveraging my
expertise in SQL, Python, Statistics, and Power BI to solve
intricate business challenges and drive tangible outcomes for
companies. I possess a strong inclination towards tackling
complex problems, optimizing operational efficiency, and
fostering organizational growth. One of the aspects that truly
invigorates me is the application of advanced machine learning
algorithms such as Regression, Classification, Dimensionality
Reduction, Segmentation, Anomaly Detection, and Gradient
Boosting. By harnessing these cutting-edge techniques, I
unlock valuable insights that inform strategic decision-making
and deliver measurable business impact.
Opportunity to Grow and Solve Challanges that will contribute to self Growth.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent

Accomplished achiever with a proven track record of success! Highlights include:
-- receiving two prestigious scholarships from top universities in New York
-- placing 2nd in a hackathon with a cutting-edge algorithm for creating personalized excursions
-- winning multiple programming contests
-- being a medalist with the Physics Junior Academy of Sciences of Ukraine
-- possessing strong math expertise in multivariate calculus, probability & statistics, and linear algebra.

Ready to bring a winning attitude and extensive skillset to your team!
As a skilled and experienced Machine Learning Engineer and Researcher, I have a passion for applying math and emerging technologies to solve real-world problems. With a recent scholarship, I am currently working on a project focused on predicting the 3D structure of proteins using their amino acid sequence. Led by Dima Kozakov, I am part of a team of experts in Applied Mathematics and Computational Biology, responsible for training, evaluating, and improving the AlphaFold model by DeepMind.

In my previous role at MindCraft, I demonstrated my ability to tackle complex challenges by predicting house prices. Working with PostgreSQL data, I meticulously cleaned and prepared features for neural networks, resulting in an impressive MAPE of 9% for sellers and 3% for buyers. I also conducted research on Object Detection and Tracking, reading several papers on contemporary technologies like CNN, Faster R-CNN, DSOD, DSSD, and YOLO.

With a wealth of experience in math applications and machine learning, I am proficient in NumPy, Pandas, SciPy, Matplotlib, TensorFlow, Keras, Git and Docker. I am deeply committed to my data science-related study projects, going beyond the task statement to develop a wide range of expertise.

My projects include forecasting time series data, utilizing statistical approaches such as exponential smoothing, AR, MA, ARMA, SARIMA, and SARIMAX, as well as machine learning techniques like RandomForestRegressor, FB Prophet, LSTM, and CNN. With NLP, I am adept at corpus preprocessing, lemmatization, vectorization, normalization, and advanced techniques such as POS and NER. I am skilled in signal processing, specializing in Spectral analysis using Fourier transform and wavelets, and linear filtering.

I have also completed business analysis projects, including working on the loyalty program renovation for a food retailer with 51 shops in the Lviv region. I am dedicated to empowering businesses with data insights and profoundly understanding their processes. Additionally, I have completed the winter school from Just Answer, where I gained knowledge in LTV, A/B testing, and cohort analysis. I have also worked on other machine learning-related projects, such as a spam filter using Naive Bayes and statistical tests, and radioactive decay of Cesium-137 using Poisson distribution.

Overall, I bring a wealth of expertise and a passion for solving complex problems, and I look forward to bringing my skills and experience to new opportunities.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: intermediate


As a Software developer (3 years), my tasks were:
• Backend development, frontend development
• Creating and consuming RESTful APIs
• Integrating third-party APIs
• Taking a part in developing handmade CMS
• Working with a project manager to provide time estimations for projects and tasks
For this job I used such technologies as PHP, MySQL, MongoDB, HTML5, CSS3, JS + jQuery.

As an assistant in university (10 months) my tasks were:
• Conduction of practical classes and laboratory work, exam assistance, guidance and counseling for undergraduate students of “Mathematical methods of operations research” course
• Supervision of 2 students with their Bachelor thesis

As a research PhD student (1 year) my tasks were:
• Descriptive and prescriptive modeling inverse heat transfer phenomena using nonparametric statistics, discriminant analysis, clustering, decision trees, probability theory, and mathematical analysis
• Problem-solving package development
For this job I used such technologies as JAVA, COMSOL, Python, Hidden Markov Model, Linear regression, Logistic regression, Neural networks
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: intermediate


As a team leader of the AI team, I analyzing and creating new task for AI solutions, also building new ML models using Python programming language. I have experience with NLP and Computer Vision solutions.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


As Data Scientist Intern for Schlumberger, I'm working on behaviour analysis, anomaly detection and predictive maintenance for a drilling tool specific to the company. The applied models make it possible to find and detect the causes of failures, act on the faulty element as close as possible to its period of failure and reconstruct the data. 
As a graduation project for SAFRAN (9 month, part-time project), I've worked on state-of-art technology, named Compressive Sensing, as well as signal processing, machine learning, regressive analysis and statistics. 
I had the opportunity to carry out several short-term projects such as Kaggle competition for Forest Cover Type Prediction, prediction of the locations of the devices for Sigfox, data analysis for GDELT database, Image Classification system, Music generation using RNN
I'm looking for the projects where I could improve my skills in Deep Leaning, Machine Learning, as well as, Cloud Computing and visualisation.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


A specialist with multidisciplinary background, obtained a PhD in engineering in EU state country, presently a data science practitioner.

Experience:
* Work on commercial projects - primarily Computer Vision-related tasks such as designing systems with object detection and classification functionality but also Natural Language Processing (Text summarization, Sentiment Analysis) and more specific tasks such as smartphone sensor data (accelerometer, gyroscope, etc.) processing and classification with neural networks. 

Additionally, have an experience with deep learning on graphs and influence maximisation.

* Internal AI research and publication - investigating the newest developments in AI area and practically applying them on problems as well as describing the results by writing articles for technology-oriented media platforms.

* Pre-sale consultations - helping clients to formulate the vision on how the AI features could be practically implemented in their product.

* Leading  1-2 data scientists on challenging commercial projects.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent

Data Science Bootcamp

The 12-week Data Science Bootcamp program is designed to demonstrate the world of Statistics, Data Analytics, and Data Science methodologies using R, Python, Spark, Spark SQL, Spark MLlib, AWS, Hadoop, Mongo DB, MapReduce, Hive, Hadoop, TensorFlow, Tableau, SPSS, SPSS Modeler and other popular industry tools.
Astute, calculating, and attentive in implementing data science to specific business requirements. Possesses analytical abilities to identify patterns, make interpretations, and produce reports. 
Skilled in predicting the future using supervised and unsupervised machine learning algorithms, and aligning
procedures with business needs.

Python McKinsey(2022)
Participant of Pro hack : International Data science Hackathon by McKinsey & Company . I was always on the lookout for machine learning projects and competitions; The McKinsey
hackathon gave me an opportunity to compete for a new job, which was a nice bonus. Plus, I was curious about the type of problems McKinsey would present. It was great experience to
compete with professionals all over the world and learn from different solutions.

Performance Analysis with Tableau(2022)
Prepared Weekly KPI performance Analysis dashboards: KPI list as Parameter, Weekly time plot of each KPI , List top 5 tariffs for each KPI and growth rate for each of them in the last week, Daily performance of each KPI in the last week, Total amount of KPI in the last week, KPI growth in last week. Prepared Daily Revenue performance Analysis dashboard by including: Total revenue, Revenue proportion of each tariff, Compare tariffs on daily basis, Visualize cluster of tariffs for the voice and data revenue. Add daily timeline of voice and data revenue for that tariff as tooltip. Portion of data revenue in the total revenue for each tariff.

ActInSpace Hackathon - Snow Satellite Data Analysis (2022)
Snow Data of Switzerland was analyzed. The main idea was to transform snow into electricity
through Geothermal Power Plant so that it will not affect an albedo
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


At Getir Company, I was a member of group which we have done route optimization, customer
segmentation, price optimization, what if simulations, sales forecasting and various other ml applications
with advanced ml models, deep learning methods and optimization techniques on multidimensional data sets
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent

I took some courses related to data science such as dataquest.io's data scientist for python and coursera Andrew Ng's Machine learning specification
Apart from that here is my education:

2023
Ulsan National Institute of Science and Technology (UNIST), S.Korea
PhD in Mechanical Engineering, Metal 3D-printing
2017
Korea Advanced Institute of Science and Technology (KAIST), S.Korea
Master's degree in Nuclear and Quantum Engineering, Refractory High Entropy Alloys (metals) for nuclear and aerospace applications
2016
Ulsan National Institute of Science and Technology (UNIST), S.Korea
Bachelor degree in Nuclear Engineering (Magna cum laude)
At Korea Institute of Industrial Technology (KITECH), 3D Printing Manufacturing Process Center, S.Korea
Researcher
- Operated industrial metal 3D Printer with metals such as SS316L, Ti Grade 2, Tool steel
- Conducted finite element analysis with ANSYS package
- Did post-processing of metal 3D-printed parts
- Conducted functional validation experimentally
- Developed cost estimation analysis via Python and assisted to the development of its website on Flask
- Classification of 3D models for 3D printing at the early design stage via Machine Learning
- Writing scientific articles and attend international&dometic conferences
I would like to gradually transition into the field of data science with my background in mechanical engineering hence firstly it would be better to start as a part-time data scientist.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


At my current job I handle supervised and unsupervised machine learning models for telecommunication and banking. For most projects I am responsible for the whole ML pipeline: data collection, cleaning, preprocessing, feature engineering&selection, modelling, validation. I also take part in deploying models to production.
Now I'm willing to move forward to more sophisticated tasks such as Deep Learning, NLP or Computer vision problems (which so far are just a hobby for me) as well as to create and/or maintain a solid end-to-end ML production systems.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper

- Built and deployed numerous ensemble models using Machine Learning algorithms
- Created from scratch ML solutions, systematize data. Thanks for my work, the company has earned and saved money.
At my current workplace I as a Machine Learning Engineer:
- Built models for credit scoring and fraud prevention using Machine Learning algorithms
- Conducted research of models performance, features generated for models to introduce further improvements
- Built models for photo-verification using different state of the art techniques. 
- Created API's for credit scoring and photo-verification.
- Been leading a team of 1 data scientist and 1 data engineer
- Deployed models in production using Docker(Kuber).

implemented from scratch different papers for computer vision which are work in production

- Created pipelines for ETL and ELT processes.
Expecting exciting research tasks that involve the use of Machine Learning algorithms. Would be interested in Computer vision oriented tasks. Especially image forensics
Position: Data Scientist
Category: Data Science
Experience: 6 years | English: fluent

- Been a speaker at multiple international conferences
- Successfully mentored 3 data scientists and mentoring now another 2
- Built and deployed numerous ensemble models using Machine Learning algorithms 
- Built and deployed 26 models prototypes for one project
- Successfully introduced CRISP-DM in the first company I've worked and adapted it in terms of agile methodology
At my last workplace I as a Data Scientist:
- trained models for credit scoring
- planned and built new deployment architecture
- managed a team of 2 developers 

At my previous workplaces I worked both as a teammate and a team lead. Twice I've gathered a team from scratch and mentored the participants. I worked in several areas such as fintech, video streaming, marketing, customer success. Over the years I've had numerous projects which involved full-cycle ML models development.
Expecting exciting research tasks which involve the use of Machine Learning algorithms. Would be interested in NLP oriented tasks. It'd be great to be a part of a team and not a lone wolf :)
Not interested in a job that involves just the development of features on the backend.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate

Passed several courses:
- Neural Networks and Deep Learning, DeepLearningAI
- Hands-on Data Science with python, Firablaze AI School
- Intro to Machine Learning, Kaggle
- Intermediate Machine Learning, Kaggle
- Advanced SQL, Kaggle
- Data Visualization, Kaggle 
- Data Cleaning, Kaggle
- Pandas, Kaggle
- Computer Vision, Kaggle
- Natural Language Processing, Kaggle
At the moment I am working on a training project related to wavelet transform and neural networks.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper

Take a look at "Working Experience" field
At the time I have 3 solid pet projects: 
1. Markov Chains-based cocktail recipes generator learned on 20k sequences corpus. All data has been grabbed, cleaned, and labeled by myself.
2. Dynamic QR codes generator made used FastAPI, aiogram, and SQLAlchemy. Telegram Bot gives you a static QR code, then using Bot you can link QR code leads and track views of it.
3. Deep-Learning-based aromatizers combiner. Trained, using one-to-many LSTM architecture, using PyTorch and PyTorch-lightning with pre-trained word2vec embeddings. Dataset grabbed and composed by myself.
I'd like to work with a modern and demanded stack of technologies, participate in solving interesting tasks that are free of bureaucracy