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


Currently, I work as a data scientist and data analyst in Prospect 33’s Global Data Lab, where I lead a project focused on predictive analytics. In this role, I develop and maintain machine learning model pipelines and use data mining, analysis, and visualization to provide meaningful insights to internal teams and stakeholders. This project has significantly expanded my predictive analytics, business intelligence, and data visualization skills. Through teamwork, we have achieved substantial profitable results. I am adept at deriving practical solutions to complex business problems through big data analysis and management.

As a Data Science Freelancer, I have gained expertise in data cleaning and visualization tools such as R, Python, Excel, PowerBI, and SPSS. I have used these tools to infer data insights and predict customer retention through sentiment analysis. Additionally, I have worked with a start-up company, where I was responsible for using data visualization techniques to increase the usability and accessibility of data for the sales and marketing departments. Working closely with other departments allowed me to hone my interpersonal skills and the ability to present complex technical information to non-technical personnel.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent

Obtained a PhD degree in economic sciences (‘Methods and models of IT project risk management’). Developed a project risk estimation model combining CCPM and Agile.

Developed a scoring model to estimate credit ratings of Ukrainian banks based on the K-nearest neighbors method with 85% accuracy
Currently, I work as a leading financial analyst and data scientist.

- Developed a model to match credit ratings of banks with probabilities of default: web-scraping (selenium, beautifulsoup), data preprocessing (pandas, numpy), data visualization (matplotlib, seaborn, plotly), model training (sklearn, tensorflow).

- Developing an end-to-end analytical system: data collection, processing and analysis, preparing decision-making data and statements (pandas, flask).

- Willing to participate in development of machine learning solutions for business to improve and extend my data science knowledge and skills.
Please don`t send me data engineer vacancies
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: fluent


Currently working as a BI Developer at a gaming startup located in Berlin.
Previous experience in Data Analysis, Machine/Deep Learning.
Education: M.Sc. in Statistics at TU Kaiserslautern, Germany.

Tech: Python (numpy, pandas, pyspark, scikit-learn, requests), SQL (MS SQL, Snowflake), R, Matlab, Looker (BI tool), Databricks, HTML/CSS.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Currently studying as a 3rd-year student at Kyiv-Mohyla Academy with an Applied Math specialization 
Participated in research work for the University of Toronto.
Attended Kaggle competitions. 
Created model for text scoring in Kaggle competition(91-93% accuracy)
Analyzed big clusters of data for commercial use.
Currently working as a Data Scientist in a big gambling company for 1.5 year.

Attended Data Science trainee program for half a year at Tallium Digital. 

Freelanced Data Science about 1.5 year

Experience with Python(4+ years including non
commercial experience)

Experience with Java, Go,R and C++
Experience with SQL databases, Clickhouse,NOSQL
databases.
Experience in Deep Learning, NLP, Data mining, Data Processing
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper


Currently working as a part-time teacher at 
GoITeens - IT Academy for teens and kids. 
Teaching children the basics of programming 
and mathematics as well as helping them 
develop soft skills.
Position: Data Scientist
Category: Python
Experience: 5 years | English: fluent


Currently working as Machine Learning Engineer in the Brazilian real estate market, focused on recommender systems, being responsible for end-to-end ML solutions. My main stack at the moment is Python, Apache Spark, Spark Streaming for the data wrangling part. For modeling I'm used to work with all the main libraries and state-of-the art models ranging from neural networks to traditional methods such as collaborative filtering. For serving I'm very well used to develop custom backends and REST APIs to deliver models at scale using Kubernetes, focusing on delivering reliable and robust solutions for the business.

I'm also learning RUST as a side language in order to teach myself a more low-level language, and also studying about causal inference.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate

I'm learning all time, like it. Low experience in Data Science, but I have a huge interest on it. All skills listed above I learned at the university and by online courses
Currently working as System Analyst in medical company. Actively using Excel and MySQL. 
Also I have experience with work on PostgreSQL, MS SQL Server
In analytics only small projects for myself to understand the meaning
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent


Current position: Data Analyst/Scientist in a product company
Key responsibilities: 
Building forecast models for companies in different industries
Creating dashboards using Metabase

I want to grow more towards NLP projects.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent


Current role: Data Scientist - NLP engineer

Projects:
NLP /NLU
Automatic Speech Recognition for low resource languages
Language modeling
AI based Chatbot 
Topic classification
Named Entity Recognition for customized entity types
Sentiment analysis for financial product reviews

Used technology: Python, Machine Learning, Deep learning. Python data processing libraries(pandas, nltk, PySpark, PyPDF), ML(scikit-learn, Pytorch, Tensorflow, Keras, Spark ML), speech processing (Kaldi), language modeling(n-gram models, neural language models using RNN) 

Would like to improve : enhance knowledge in signal processing and speech recognition fields
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper

Successfully passed the Microsoft DP-100 exam: Designing and Implementing a Data Science Solution on Azure.
Customer analysis and demand forecasting projects for a big retail company. Responsibilities:

• Implementing transforming pipelines from the raw data in the database to the machine learning models.
• RFM (Recency, Frequency, Monetary) customer analysis with the rolling time window.
• Churn prediction, anomaly detection, customer lifetime value (CLTV) prediction ML models.
• Customer's product basket and association rules analysis.
• Analysis and search for the analogues of product and store newbies (items with insufficient sales history).
• Developing ML model for demand forecasting


Risk management project for the foreign bank:

I have carried out quantitative analysis to determine the value of financial agreements such as swaps, forwards, futures, options. It helped the client to decide whether to make the corresponding financial agreement or not.

Mini projects:

• Estimation of the car price according to its sale advertisement (web scraping, REST API, machine learning model)
• Computer vision: detecting the information on the product's price tag (price and barcode)
Actively growing companies and projects
Team brainstorming for the challenges solving 
Computer vision and/or voice recognition tasks would be a plus
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Customer Churn Prediction
 Machine Learning (ANN)
•	Built a model that could predict customer churn for a bank using Artificial Neural Networks and in the long-run know which clients were at risk of leaving the bank.

Standard Bank 
 Data Science (virtual internship)		
•	Implemented a model that predicts whether a potential borrower will default on his or her loan or not. 
•	Used machine learning to evaluate an applicant’s worthiness and streamline the process so that the applicant hears right back away after submitting their application rather than having to wait 2-3 days. 
. 
Sales Exploratory Data Analysis
 Python
•	Did some exploration using Pandas and NumPy on sales data where I answered questions relevant to the business, that included: What products are often sold together? And, what time should ads be displayed to maximize likelihood of customers buying the product.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


- Customer Data Platform & Warehouse development: building scheduled queries and cloud functions on GCP;
- Customer performance evaluation model: based on users activity data, developed anomaly detection model (IQR method); 
- Entity recognition: developing the mechanism which is able to recognize different representations of a particular entity in the text data and cluster them into one group;
- Time series analysis;
- Scoring model development: based on the participant's information, developed a statistical algorithm, that produces an evaluation score for each participant;
- Sentiment analysis, text data mining: performing a set of cleaning techniques, text data analysis, building sentiment prediction model with BERT;
- Object segmentation, tracking, replacement R&D (basic experience with OpenCV).

All the projects are covered with the following libraries\frameworks:
- Handling data with Pandas, NumPy, SciPy;
- Data visualization with Matplotlib, Plotly, Seaborn;
- Developing basic ML models with Scikit-learn;
- Working with text data with NLTK, Spacy, BeautifulSoup;
- Developing Deep Learning models with Keras, Pytorch, Transformers.
I'm looking for a job in a product company with an interesting project and with the objective to improve someone's performance and simply make our life better.
Preferred fields of activity are Machine Learning\Deep Learning, NLP.
Position: Data Scientist
Category: Python
Experience: 5 years | English: fluent

I have performed data analysis and built financial models that have been integral projects totaling $100million.
Data Analysis, Finance, Python, Machine Learning
I am looking for a junior data scientist role as I have moved to the field of machine learning over a year ago.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: pre


-- Data Analysis Projects --
As an aspiring Data Scientist, I took part in several projects:

• October 2022. Completed a two-month project as a Data Analyst for an online-education platform. Analyzed and overhauled the reports of the Marketing dep., introduced more efficient analysis scheme, hence -- reduced report preparation time for the managers from 4 hours to 10 minutes.
• July 2022. Participated as a freelance data analyst in a statistics gathering project. Applied knowledge of SQL and Agile methodologies for statistical research on Ukrainian refugees in different world countries.


-- Project Management --

• On a monthly basis, completed technical research and estimations for construction and equipment-manufacturing projects in 2016-2021.
• As a part of industrial projects team, my colleagues and I successfully implemented 10+ commercial construction projects worth $ 500K - $ 8KK.
• Conducted an expert assessment and revised 400+ TORs based on project documentation, which helped speed up the search for contractors and reduce the overall time for projects implementation.
• Introduced Agile methodologies (Kanban system in Asana) into the workflow of the Design & Construction department within one month.


Education and certificates:
• Master's degree in electrical engineering from Donetsk National Tech University (2011-2018).
• Online Certificate "Data Science from scratch" (ongoing education till March 2023).
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: intermediate


Data Analyst, 1 year 6 months:
- created pipeline for time series prediction based on econometric model
- created automatic reports for gathering, merging and aggregating data from different data sources 
- created linear regression model for subscription renewals predict
- created anomaly detection system based on confidence intervals
- making data-driven decisions for improving product quality and KPI’s

Skills
– Machine Learning Concepts: learning theory (fitting models, validating and testing), EDA, pipelines for gathering and clearing data
– Statistics: hypothesis testing, confidence intervals
– Time series: decomposition, anomaly detection, ARIMA and other econometrics models
– Product Analytics: pyramid of metrics, market funnel, A/B testing for funnel optimization, SaaS met- rics and KPI’s, cohort analysis
– Analytics Systems and Warehousing: ETL, data warehousing, Google Analytics, Pentaho
– Python & Python libraries (NumPy, SciPy, MatPlotLib, Pandas, Sklearn)
– Keras
– SQL: PostgreSQL, MySQL
– C / C++
– Git, Jira
– English (upper intermediate)
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper


Data Analyst|Data Scientist
OLX Group
Aug 2021 - Present · 1 yr 7 mos
Kyiv City, Ukraine
- Developing and supporting ML model for the text similarity detection
- A/B testing
- Research for the user segmentation model
- Making ETL pipelines and analysing data from external sources
- Competitive analysis
Skills: Python (Programming Language) · Analytical Skills · Data Science · PostgreSQL · MySQL · R (Programming Language) · Amazon Redshift · Jira · Gitlab · Tableau
-------------------------------------------------
Business Consultant
McKinsey & Company
Oct 2021 - Dec 2021 · 3 mos
- Market research of metal mining companies in Kazakhstan
- Analysis of historical data and metal price forecasts
- Analysis of negative factors, production processes and the market
- Short-term and long-term initiatives to increase the company's revenue
Skills: Consulting · Price Forecasting · Business Strategy · Strategic Planning
---------------------------------------------
Machine Learning Researcher
Computing Center of the Academy of Sciences
Aug 2020 - Jul 2021 · 1 yr
- Development and training of a model for extracting information and characters from texts
- Development of ML project "External Plagiarism Detection", detection the anomalies in the statistics and the activities that exceed thresholds of the deviations using TfidfVectorizer and cos similarity
- Participating in development of the Service for Recognizing Tabular Data Based on Open-source OCR Tools. The project involved the use of OpenCV and Tesseract to recognize images and the texts in the images
Skills: Python (Programming Language) · Machine Learning · Data Science · Databases · Science · Research and Development (R&D) · Data Analysis · Research · Natural Language Processing (NLP) · Applied Machine
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

- participation in Neurohackathon (hors concours).
- feature engineering and Big Data preprocessing for the healthcare project
Data Analyst in a Data Science team responsible for exploratory, statistical data analysis, and visualization, feature engineering, preparing data for the models and engaged in models development. 

Experience: 9 months

Stack: Python, Pandas, Scikit-learn, NumPy, StatsModels, Matplotlib, Keras, Seaborn, Plotly, Dash, Tableau, PySpark, Bitbucket, Jira, Selenium.

Key responsibilities: 
• exploratory data analysis
• data preprocessing
• feature engineering
• statistical analysis 
• visualization

Additional responsibilities:
• machine learning models development

Projects:
1. Computer Vision domain. Developing a realtime webcam face recognition tool based on OpenCV libs. The tool defines unique faces, their age and gender, tracks emotions and builds an analytical dashboard.
2. Urban domain. Developing a visualization module based on Dash and Plotly. The module aims to provide daily human mobility analysis of different city zones using telecom data and show the most popular routes.
3. Agriculture domain. Building the yield forecasting model based on historical yield data, historical weather data, and protocols about crop favorable growing conditions. 
4. Healthcare domain. Exploring medical protocols and creating association rules based on symptoms, comorbid conditions and laboratory analysis for revealing diseases unnoticed by doctors.
5. Automotive domain. Developing a part of the recommendation system based on statistical analysis.
Strongly interested in diving deep into Data Science and designing complicated machine learning solutions.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent


DATA ANALYST · NetLime · Freelance (Mar 2019 – Present) · Kyiv
 - data mining with ML packages and SQL, trends or clustering interpretation;
- solving business problems with proper result visualizations;
- deep research of clients information, correlations and opportunities detecting;
- needs-based optimization and applying of data algorithms.

SALES EXECUTIVE · Megalamp · Full-time (Apr 2014 – Present) · Kyiv

DEPUTY CHIEF · UniCredit Bank Ukraine · Full-time (Dec 2007 – Sep 2011) · Donetsk
- supervision of branch sales and operational activities, SMEs operations;
- negotiations with partners, true customer needs assessment and selling;
- loan preparations to Credit Bureau, maintenance and risk management processes. 

CHIEF ECONOMIST · Raiffeisen Bank Aval · Full-time (Apr 2007 – Dec 2007) · Donetsk

INVESTIGATIONS SPECIALIST (Processing Center) · First Ukrainian International Bank · Full-time (Jul 2003 – Apr 2007) · Donetsk
- fraud monitoring of card transactions; client support; problem resolution and communication skills.
Position: Data Scientist
Category: Data Analyst
Experience: 1.5 years | English: fluent


DATA ANALYST with 1.5 years experience
advacned Excel /VBA
advanced Power BI
advanced SQL skills
intermediate Tableu skills
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


Data Analyst with more than 2.5 years of commercial experience mostly in Assurance and Fintech. Throughout my career path I held positions at Big-4 (EY) as well in product companies (Maxpay), where the scope of my responsibility were as follows: 
- automation of the reporting process
- company KPI analytics and forecasting
- support the planning, execution, and delivery of assurance engagements.

In my day-to-day activity I leverage the following tech stack: 
- SQL 
- Python (Numpy, Pandas)
- AWS (Athena, QuickSight)
- Tableau
- Excel, PowerPoint
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: pre

Searching skill is better for me and also it is funny to find new information or define business problems and solve them.
Data analytics Remote
Quantium Co
City: USA Californiya
Data preparation and customer analytics. End to end project. analyse data and use ML algorithms to predict data.

Data analystics Remote
British Airways
City: UK London
Data preparation and customer analytics. Web scraping to gain company insights. Predicting customer buying behaviour using ml algorithms. Create sentiment analyze and word cloud to predict short insight customer about company.


Business analytics Intern
Taskilled
City: Azerbaijan Baku
To get information about data. Detect problems on business solve problem, provide insight for business
I can apply my data science skills in the all business no matter the sectors.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Data Analytics using Pandas and Dashboards with Power Bi retrieving data using SQL.
Classification algorithms for predicting credits loss default in Python (using scikit-learn) for a company in the banking industry
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper

I have built convolutional neural networks for image classification tasks and text summarization comparison project using python and data science frameworks as a bachelor/master degrees thesis works. I've acquired competence in statistics, theory of probability, optimization, machine learning algorithms. 

I have participated in the international program for mathematicians and engineers (1-year course abroad that was taught in English).
Database analyst:

My responsibilities are: queries to the database, administrating the database and the data lake, creating reports, writing technical requirements to the developers and BI teams, discussing with clients their requests, issues with the system, and needs.
I expect to mainly work with data i.e. extract, transform and give an insight into it. Also, concentrating on one part of that process is also interesting for me, as a big data engineer, for example.
Position: Data Scientist
Category: Data Analyst
Experience: 3 years | English: fluent

• Utilized Tableau to analyze sales and income KPIs and delivered insightful reports to 7+ stakeholders, contributing to a 15% increase in sales and a 20% boost in revenue.
• Achieved a 12% YoY increase in customer acquisition by developing and operationalizing multivariate regression models that accurately predict portfolio losses based on macroeconomic forecasts.
• Led the end-to-end development of predictive models by creating SQL databases, automating data queries using ETL, performing imputation, normalization, preprocessing (utilizing PCA and PCR), and optimizing the models to enable effective product analysis.
• Implemented a Data MART that efficiently processed and organized daily data sets of up to 15 million rows and pivoted to a Revenue Fact Table for Bank products such as mortgage, cash credits, credit cards and etc.
• Mentored and supervised 3 interns in conducting research on evaluation metrics, variable selections, and cross-validation visualization dashboard, resulting in widely adoption by multiple teams across the Bank. The success of the research led to the interns being offered full-time positions.
Data Cleaning on Electricity Usage Data with Python
In this project, I have been provided with data on Electricity Provider
Company. As data was in an unstructured and unsorted format I had to clean data and turn it into a usable format. My second task was to select an optimal contract based on usage history.

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 the last week
Analytically minded and proactive Data Analyst with 3+ years of industry experience, adept at collaborating with cross-functional teams to deliver accurate and reliable data-driven insights for high-impact projects.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper

Candidate of Physical and Mathematical Sciences (Ph.D.) 
Postdoc in University of the Basque Country, Bilbao, Spain (grant awarded from Erasmus Mundus ACTIVE programme)
Data collection from various sources: energy prices, climate data, electricity demand and consumption. 
Data processing and creation of data sets. 
Statistical data analysis. 
Development of time series forecasting models in Python - SARIMA, SVR, Random forest regression, RNN neural networks (LSTM, Encoder-Decoder model with Bahdanau and Luong 
attention mechanisms)