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


I began my career in 2019 as a Business Analyst at Air Astana, the largest airline in our country. I got this opportunity through a competitive internship organized by the National Welfare Fund of the Republic of Kazakhstan. During the internship, I worked on implementing processes for the Purchasing and Ground Services Departments using the ELMA BPM system.

In 2020, I interned as a Data Analyst at Kolesa Group, a leading company in the classifieds business. I created useful dashboards and conducted tests to improve conversions, such as achieving a 2.5x increase in Auto Credit sign-ups.

Later, I joined KazMunayGas Engineering as a Software Engineer in the Big Data sector. I focused on managing data in the MySQL database and developing backend features for monitoring company performance.

Currently, I work as a Data Scientist at Technodom, a major electronics retailer. During the work we leverage diverse customer data, including external data parsed from various sources. I have executed projects encompassing NPS classification, churn prediction, next purchase prediction, and demand forecasting. These initiatives involve comprehensive data analysis to generate valuable insights and predictions, enabling informed decision-making. We also utilize AWS for efficient data storage and analysis.
• Working with an international team
• New challenges
• Learning new technologies
• Solving big scale problems
• Looking for data science/data engineering/data analyst positions
Position: Data Scientist / Data Engineer
Category: Data Science
Experience: 5 years | English: fluent


I have 5+ years of experience working in data science and machine learning field. My experience covers different industries, such as Banking/Fintech, AI consultancy, Food Delivery/Quick Commerce, Talent Management, Cyber Security, Software Development, etc. During these years, I gained valuable hands-on skills in data science, machine learning, and software engineering fields.

Few projects I've worked on:

Cyber Security
- Anomaly detection model to identify possible abnormal behaviour observing windows events.

Search Engine:
- Build and productionized search engine where I extract tens of thousands of data points in real time and rank them using different measures. Here, I mainly do data engineering stuff.

Matching Engine
- Build matching system to match job description to job candidate and vice versa.

Anomaly Detection Model
- Build real time anomaly detection model for time series data
- Build time series similarity measure model to identify "sister" (similar) time series.

Question-Answering Model
- Build and deployed QA model to process PDF documents and provide answers to the pre-defined list of questions.

Credit Scorecard Model
- Build credit scorecard model to automate loan disbursement process
- Conducted market basket analysis to reveal customers new segment

Find a lot more info in my CV.
I'm looking for new challenges. Where, I will gain new skills, will learn new technologies, and will grow professionally in every direction. The place and the team, that have can do and everything possible attitude. They share their experience and help team members to improve.
Position: Data Scientist / Data Engineer
Category: Python
Experience: 5 years | English: fluent

- Kaggle: Santander Product Recommendation [TOP 15%],
House Prices: Advanced Regression Techniques [TOP 4%]
- Have built a web-crawling agent that allows to retrieve automatically text of all job openings found on indeed.com and linkedin.com websites with respectto user request (job title, place, salary, etc.). Advanced filtering involves NLP (stemming, lemmatization, Ngram) and regex for text cleaning, TF-IDF algorithms for feature extraction. The result - one can plot, for instance, top-X skills required for any position in any city or country in the world. Steck of technologies: Python (nltk, BS4),
PhantomJS, Selenium.
- Deployed from sketch Hadoop 2.x ecosystem on multi-node cluster: HDFS, YARN, Pig, Hive, Hbase, Sqoop, and Spark.
Key expertise:
• Python: 5+ years, Hadoop ecosystem: 2+ years. 
• Fluent English, Intermediate Italian and French.
• Machine learning (classification, regression, clustering): 2+ years. 
• Web crawling (Python, requests, BS4, PhantomJS, Selenium, NLTK, regex).
• Design and implementation of Batch jobs using Sqoop, Hive, MapReduce and SPARK.
• Development and running of SPARK applications on Hadoop YARN multi-node cluster using Python (analytics on data, ML tasks).
• AWS EC2. 
• RDBMS (MySQL), NoSQL (MongoDB, Apache HBase). 
• PhD in Engineering (Italy).
• Currently employed in EU.
- Challenging projects using latest steck of Big Data technologies and frameworks 
- Excellent working environment
- Location of the office: UA (Lviv or Kyiv)
Position: Data Scientist / Data Engineer
Category: Data Science
Experience: 11 years | English: upper


Strong data scientist with experience in software development. 

Professional skills:

- Good experience in predictive analytics
- Comprehensive knowledge of data validation and data analysis process and techniques
- Broad experience in the financial services industry and multi-disciplined wealth management expertise
- knowledge of PM-book standards for developing project management documentation, Jira, Scrum, Agile

Technical Skills:

- Proficiency in statistical and mathematical packages: SPSS, SAS, R, R-Studio, Python
- Python, Tensorflow, Keras, PyTorch, Pandas, scikit-learn etc
- Experience in DB: Sybase IQ, MSSQL, PostgreSQL, MySQL
Position: Data Scientist \ Data Engineer
Category: Data Science
Experience: 3 years | English: upper


Passionate developer with 4+ years of experience in Python programming, focused on Data Science for the last 3 years, mainly in the biomedical industry and wearable devices.

Worked on R&D of DL\ML\classical algorithms for biomedical signal analysis(mainly 1D-like signals like Respiration, ECG, PPG, etc), working on tasks of data exploration and visualization, segmentation, classification, tools for data labeling, classical algorithms optimization with Cython, report generation, testing tools, working with SQL databases.

Have experience turning algorithms into microservices (Flask\aiohttp\gunicorn\docker), some minor experience with GCP\Microsoft Azure.

Having wide experience in different fields, I can be a Data Scientist, Data or Backend Engineer, or both of these roles.
Position: Data Scientist, Data Engineer
Category: Data Science
Experience: 3 years | English: upper


Analyse data • Collect data • Prepare regular reports •  Design and develop reports, BI dashboards • Provide 
Top Management team with deep insights regarding company and applicable activities • Support in decision-making • Data analysis to detect the reasons for deviations in the main and secondary metrics • Bringing early attention to issues or changes in trends related to KPIs • Ensure that data is tracked in the proper manner • Looking for alternative data sources and tools • Collect data from different place• Design and develop dashboards, repots (MS Power BI) • Create visualizations and presenting them to the team and management

Analysis • Power BI • Data Analysis • SharePoint • Power Automate • Power Apps • Tableau • Statistica • SAP • MES • SPS • GIT
Position: Data Scientist, Data Engineer
Category: Data Science
Experience: 5 years | English: fluent


Data Scientist Network, Lagos, Nigeria.
Data Scientist 
	Built an end-to-end computer vision model that could classify Community pharmacies (CP) and Proprietary Patents and medicine Vendors (PPMV) stores in local areas in Nigeria using Python, TensorFlow, Keras. 
        Built a Retail audit Computer Vision model using YOLO architecture to recognize over 500 FMGCs products in Nigeria, determine the visibility and provide detailed analytics based on the detected FMCGs products (PyTorch, TensorFlow, FastAPI).	 
        Design and implement end-to-end data engineering pipelines to acquire, prepare, and store data in the data warehouse using data engineering standards (ETL/ELT).
	Develop a detailed project plan identifying the key milestones, resources, deliverables and track project KPIs over time.
	Develop real-time analytic dashboards using Power BI for insightful decision-making and to track project progress.

MeasureIT Analitika, Ibadan, Oyo State, Nigeria.
Data Analytics and Visualization Associate
	Designed and developed an interactive dashboard to track and evaluate key performance indicators using Tableau, Microsoft Power BI, Microsoft Excel, and Google Sheet
	Prepared and coordinated monthly analysis and visualization.
	Reviewed, cleaned, and validated converted datasets for possible insightful analysis. 
	Supported the development of the Multi-source Data Analytics and Triangulation dashboard.
Position: Data Scientist, Data Engineer
Category: Data Science
Experience: 11 years | English: intermediate


For the last year, I've been working in the R&D department of a Ukrainian retail company as a Data Scientist.
Before that - two years as a freelancer Data Analyst / Data Scientist via Upwork. Earlier - 8 years in scoring models' development, risk management, and banking analytics.
My main tools are Python and SQL, used to work with R. 

My last projects:
- an auto-replenishment algorithm, with a short-term sales forecast for supermarkets. Python, Jupyter Notebook, Time Series Forecast, MS SQL Server, Azure DevOps;
- KPI metrics for employees and supermarkets. Power BI, MS SQL Server;
- customer journey analysis, marketing attribution models. BigQuery, Python, SQL, DBT, BitBucket, Hubspot;
- ad-hoc analysis and dashboards on retention, conversion, sales, customer structure, helpdesk, and email campaigns, designing experiments in prices, discounts, and free products, developing mix marketing, attribution, and customer churn prediction models. Python, BigQuery, Google AutoML, Periscope / Sisense, R, Zendesk, Fullstory, Mixpanel, Shopify, Stripe, Blendo, Xero.
Position: Data Scientist/Data Engineer
Category: Data Engineer
Experience: 5 years | English: fluent


Data Engineer/Data Modeller/Data Scientist(healthcare domain) 03/2022 - present
- Data Modeling;
- Looker refactoring;
- Communication with stakeholders;
- Data Science tasks(e.g. classification, topic modeling);
- Documentation maintenance;
- Hands-on technology stack: AWS, Snowflake, Looker, dbt, Snowshu, AWS SageMaker, Great Expectations, Confluence, Jira, Bitbucket, DBeaver, Docker, Python(pandas, numpy, sklearn, nltk,TensorFlow/Keras, PyTorch,XGBoost, seaborn/matplotlib and etc.), SQL, Anaconda.

Data Analyst(financial domain) 09/2020 - 03/2022
- Analysis of Macroeconomic data across the globe;
- Provide Data/Customer support using ITIL framework;
- Researching data, insights on the internet;
- Communication with Customer/Data providers on their/our needs as a service provider;
- Data Engineering;
- Extra mile: successfully passed internal Data Science Mentoring program and able to do: EDA, Hypothesis Testing, Regression/Classification tasks, Clustering, Anomaly Detection, NLP(text), Time Series Forecasting, NN and CV, NN and NLP(text)
- Hands-on technology stack: AWS, ServiceNow, Confluence, Jira, Swagger, Rundeck, Hbase, Postman, Kibana, Python(bs4, selenium,pandas, numpy, sklearn, nltk,TensorFlow/Keras, PyTorch,XGBoost, seaborn/matplotlib and etc.), SQL, Azure ML;
Position: Data Scientist/Data Engineer
Category: Data Science
Experience: 8 years | English: upper

Azure Data Scientist Associate

Coursera specialization:
Machine Learning & Data Analysis Specialization
Deep Learning Specialization
Algorithms specialization by Stanford University
Data Scientist/Data Engineer with math background and 5+ years of experience in building data-driven solutions (7+ years in software development in total). Passionate about solving different problems alongside learning something new.
For most of my relevant experience, I worked for an outsourcing company(Big Data and Analytics). As a member of the R&D department, I worked on mostly short/mid-term projects and internal ones for the company itself. 
My experience is balanced between Data Science and Data Engineering, sometimes dealing with both roles on the same project. you can find details on the latest projects below.

Data Engineering Projects – Databricks Engineer
- Project result: Speeding up an existing e2e solution by 10x times using big data  tools and frameworks
- Designing and implementing ETL workflows for collecting structured and semi-structured data
- Building Quality Control framework for data cleansing
Tech stack: Python, PySpark, SQL, Databricks, Azure platform

Sales Forecasting Project – Data Scientist/ Data Engineer
Project result: developed helper tool for the sales department, which is used for decision-making process 
Designing and implementing ETL workflows for collecting data
Building ML solution to forecast product sales based on early market lifetime
Tech stack: Python, ​Pandas, Scikit-learn, XGBoost, Azure platform

Employee Leave Forecasting – Data Scientist
Project result: developed PoC helper tool for the HR department
Parsing and collecting data from different sources (Databases, excel files, third-party APIs)
building ML models to predict employee leave
Tech stack: Python, ​Pandas, Scikit-learn, XGBoost
Position: Data Scientist/Data Engineer
Category: Data Science
Experience: 0 years | English: upper


I had experience in commercial projects as Unity Developer (C#). Along with good code-style practices I also gained experience in the product development cycle and working in a team. 

When it comes to working with data, I have experience with Python (including relevant tools for engineering: Kafka, PySpark, MongoDB, and as well for data analysis and machine learning: Pandas, Numpy, Scikit-learn, Scipy)

I have a few pet-projects working with all those technologies, including:
- Image Segmentation (Research and comparison of algorithms, working with CNN + PyTorch implementation)
- Wikipedia Data Stream Processing (Implemented system which processes Wikipedia stream data with the further access to it from REST API endpoints using Apache Spark Streaming, Kafka, Cassandra, FastAPI)
- Matrix factorization (collaborative filtering) for recommendation systems (explore the use of matrix factorization techniques for collaborative filtering in recommendation systems - implementation of Singular Value Decomposition, Non-negative matrix
Factorization and Alternating Least Squares algorithms.)

I'm interested in growing in this direction and learning new things.
Position: Data Scientist, Data Engineer, Data Analyst
Category: Python
Experience: 1 years | English: upper


Production Engineer intern
Azertexnolayn 

Observing technological processes in the workplace, recording and reporting problems that occur during production process, controlling equipment, and other necessary actions providing the continuity of production and operations.

Data Analyst intern
AZBADAM LLC | 18/10/2020 - 10/04/2021

 I used analytics tools such as Power BI and Python to create forecast analysis and reporting.
 My responsibilities were:
Interpreting data, analyzing results, using statistical techniques and providing ongoing reports.
Analyzing data and present data through reports that aid decision-making.
Locating and defining new process improvement opportunities.
Position: Data Scientist/Data Engineer/Data Science Team Lead
Category: Data Science
Experience: 11 years | English: upper


15+ years of experience working with data.
Programming languages: R, Python, SQL;
Skills: geospatial analysis, prediction models, behaviour prediction, process mining, recommender systems, NLP, deep learning, web scraping;
Сloud computing: AWS, Google Cloud Platform;
Databases: PostgreSQL, MySQL, Mongo, Redis, DynamoDB, AWS Athena/PrestoDB, ElasticSearch, etc;
Frameworks: Tidyverse, Scrapy, Numpy, Pandas, Sklearn, Tensorflow, Keras, Pytorch, Airflow, etc;
Web: Flask, Django, CoffeeScript, Flexdashboard, Shiny;
Cluster computing: Apache Spark;
Geospatial: Postgis, QGis, R packages, geopandas;
Project management: Scrum, Kanban, LeanDS;
Other: Docker, Git, Jira/Trello, Nuclino.
Position: Data Scientist | Data Engineer | Machine Learning(ML) Engineer
Category: Data Science
Experience: 2 years | English: fluent


Data Scientist with a strong statistical background and 2+ years of experience in predictive modeling, data processing, data visualization, and data mining algorithms to solve challenging business problems. Highly motivated in delivering data-driven and customer-centered software applications. Proficient in Python programming, SQL, data visualization with Tableau, statistical modeling, and applied machine learning in production. Experienced in preprocessing, cleansing, and validating structured and unstructured data for further analysis.

I would describe myself as driven, hardworking, resilient and resourceful individual who maintains a positive, proactive attitude when faced with adversity.

KEY COMPETENCIES:
•Python(Programming language)
•C++(Programming language)
•R(Programming language)
•Java(Programming language)
•SQL
•Data visualization with Tableau
•Statistical modelling
•Applied Machine learning in production
•Deep Learning using Tensorflow and pytorch
•Web scrapping using beautiful soup and Scrappy 
•Data structures and Algorithms in C++/Python
•Big Data Analysis and big data tools(Hadoop,Apache spark,pig and Hive)
•Cloud computing-Amazon AWS
•Natural Language Processing (NLP)
•Data warehousing and ETL tools(Talend)
•NoSQL DBMS -Mongo DB and Hbase
Position: Data Scientist / Data Engineer / ML engineer / Deep Learning engineer / Python Developer
Category: Python
Experience: 0.5 years | English: intermediate


I have 1.5 years of experience in the field of financial analytics. For the last year I have been engaged in in-depth study of machine learning on a python, mainly computer vision.

Now I'm working on pet project. It's about object detection and trajectory tracking using YOLO and KalmanFilter.
For a now I am open to any projects, especially in a friendly and cheerful team.
Position: Data Scientist | Deep Learner
Category: Data Science
Experience: 3 years | English: upper

Strengthen the case of using generative networks for fast simulation and demonstrate that physically relevant differential distributions can be described with high accuracy.

WILD WILD HACK finalist by Reface & Pawa.
I am a Deep Lerner with strong background in experimental physics and 3 years of  proven experience in DL/DS projects.
Position: Data Scientist, Deep Learning
Category: Data Science
Experience: 0.5 years | English: upper


Oracle, MSSQL, SQL, PLSSQL, Jira, Svn, Virtual Servers, HTML , CSS, PHP, JavaScript
Whant to take part in DataScience company to have oportunity in working with Data
Position: Data Scientist/Deep Learning
Category: Data Science
Experience: 3 years | English: fluent

Without using pre-trained solutions, only raw papers and understanding of signal itself, built solution in 2.5 years which now is used by different clients all over the word. 
Started as trainee, now leading a small team.
The project I am working on is different signals interpretation using NN. The project itself was built almost from scratch. At the start, I was only responsible for building and training nets and pre/post-process backend. Also, I am responsible for analytical backend of our product which gives necessary statistics for our customers. I am in charge of all Python-related backend(including NN), I cooperate with other teams and consult clients about how our algorithms work.

Neural nets construction, training and validation(tensorflow, pytorch). CNN, tranformers, GAN.

Python is my main instrument. In-depth understanding of scientific stack(numpy, pandas, scikit,...) for solving different problems; good understanding of common backend libraries(RabbitMQ, proto, grpc) which have been used for I/O between different services; also a big fan of numba and CuPy for time and memory optimizations. 

SQL, noSQL
Nothing related to "how to score even more money for our business".
Couldn't stand discrimination in any form especially at work.
Position: Data Scientist / Developer / Linguist
Category: Data Science
Experience: 1.5 years | English: fluent


Passionate data scientist / developer with 1.5+ years of experience in python programming, predictive modeling, data mining, and visualization.  Strong background in both applied and theoretical linguistics with over 15 years of experience. The main area of focus is natural language processing (NLP). Refined relationship-building skills and experience working collaboratively with multicultural partners and customers in various international projects.
Position: Data Scientist / DevOps
Category: DevOps
Experience: 5 years | English: upper

Participation in “Country level demonstration of Sen2Agri in Ukraine” within
European Space Agency (ESA) project “ESA Sentinel2-
Agriculture” (2016-2017) and FP7 project “Stimulating Innovation for Global Monitoring of
Agriculture and its Impact on the Environment in support of
GEOGLAM” (SIGMA) (2013-2017)
Data Scientist, EOS Data Analytics
2017 - Present

Lecturer, National Technical University of Ukraine "KPI"
2010 - Present
Lecturer (2010-2014), Senior Lecturer (2014-ongoing)
Disciplines: Computer Sciences, Intro to data science,
Programming, Machine Learning

Scientist, Space Research Institute NAS Ukraine and SSA Ukraine
2010 - Present
Leading Engineer (2009-2012), Junior Research Scientist (2012-
2013), Research Scientist (2013-2014), Senior Research Scientist
(2014 - ongoing)
New experinence in cloud computing, data processing etc.
Further self education in R&D domain and DevOPS area
Position: Data scientist / Econometrist
Category: Data Science
Experience: 1 years | English: fluent

- Achieved an accuracy of crop (yield) prediction in Ukraine and 2 neighbouring countries at 90% for 2 years in a row.
- Forecasted the 3-month price of several commodities with 85-88% accuracy.
My analytical and data science experience mainly deals with agricultural markets (commodity trading). I've been responsible for crop prediction & modelling, trade flows forecasting as well as estimation of future paper/physical prices using both conventional MS Office tools and programming software (Python, R). I am quite proficient in econometrics methods (feature engineering, regression analysis, clustering, heat maps) and comfortable with developing and improving ML/DL algorithms.
Looking for new opportunities and challenges in the field of data science, preferably where I can utilize my econometrics and ML/DL skills.
Position: Data Scientist engineer
Category: Data Science
Experience: 1.5 years | English: upper

My team and I developed an algorithm which provides performance comparable to the state of the art model.I wrote an article and going to present it at the conference in April
I'm working at Samsung Electronics company
Our department focuses on research and development ML algorithms for health/fitness devices

Now I'd like to work on tasks related to Natural Language Processing  or Image Recognition
I'm attracted by dynamic working flow, both research and development. I will favour ML projects (not connected to the ads) and additional software developing tasks 

Medical insurance, gym, language courses are preferable