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


Experience
Trade representative
from 09.2021 to now (10 months)
• "OLGA-LOGISTIK" LLC• AB InBev Efes Ukraine, Kyiv (Low-alcohol drinks)

Work with national and local networks, Novus, Metro, MegaMarket, Pchelka, Lotok, ECO.
Conducting negotiations, monitoring promotional activities, monitoring contractual obligations, setting goals for merchandisers, document management, reporting.

Trade representative
from 04.2021 to 09.2021 (5 months)
MASHPROM Bianchi LLC, Kyiv (Coffee Direction)

Development of active client base (retail), territory - right bank of Kyiv. responsibilities: installation/removal of coffee equipment and maintenance (repair, service, adjustment), conducting demonstrations and tastings, control of coffee ingredients, collection of statistics, orders and delivery of goods, cash collection, reconciliation with clients, work with receivables, document management, reporting .
Installation of marketing materials (arakal, billboards, posters, banners, price tags).
Implementation of the sales plan.

Trade representative
from 12.2020 to 04.2021 (4 months)
BELLIF LLC, Nestlé Professional, Kyiv (Coffee Direction)

The main task was to visit retail outlets, collect statistics from coffee equipment, control coffee ingredients, control the technical condition of the equipment, and work on increasing sales and maintaining long-term relationships with customers.
Participation in the launch of marketing actions.
Trainings for baristas.
Work with document flow and accounts receivable.
Search for new clients.

Head of the Service Quality Development Department
from 07.2019 to 04.2020 (9 months)
JSC Ukrposhta, Kyiv (logistics, transport, postal services.)

Ensuring the development of the postal network (more than 11,000 branches).
Development and implementation of modern consumer service technologies in order to improve their quality and sales efficiency.
Management of sales efficiency processes and their optimization.
Ensuring performance indicators of each employee of the division involved in the network development process.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: intermediate

Internship Student - DataRoot University • Kyiv 
2017-10 - 2018-04 
Intensive Data Science trainee Program where you learn the theory needed for any full-cycle data science project development:

- Python for Data Science (math & libs, python practice. tableau)

- Machine Learning (supervised learning, unsupervised learning, scikit-learn)

- Deep Learning (deep neural networks, computer vision (CNN), sequence models (RNN), keras, tensorflow)

- Big Data & Data Storages (data mining algorithms, data storages, visualization tools)
To consolidate the covered material, I took part in the Kaggle competition, where according to results I entered in the top 100.


Sentiment Analysis of Social Media in Russian • Kiev 
2018-10 - 2018-11 
The task was to build a multi-headed a model that’s capable of detecting different types of sentiments in Russian VKontakte posts. For this task RuSentiment dataset was used. RuSentiment is currently the largest in its class for Russian, it contains 30,521 posts and wich are divided into 5 classes. 
To solve this task I use pre-trained vectors for russian language trained on Common Crawl and Wikipedia using fastText. 
The best performance was RocAUC score of 0.88 in 5-class classification on the test set. It was achieved by a CNN classifier with in-domain FastText embeddings. 
Technologies used: CNN, RNN, Logistic Regretion, fastText, Tf-idf, Word2vec

Recognizing text from a document photo
2019-05 - 2019-09
The task was to create a chatbot that could recognize certain text fields in a document from a photograph. As a result, my program was able to correctly recognize more than 90% of the documents from the test data set. This gave a huge leap in productivity and saved a lot of time and money for the company in which I worked.
Technologies used: CNN, OpenCV OCR, Tesseract, Google Cloud, Heroku, Telegram bot API
- Experience with Python (Pandas, Numpy, Scikit-learn, Scipy, Seaborn, Matplotlib)
- Math (statistics, the theory of probability, linear algebra)
- Machine Learning algorithms (Decision trees, Naive Bayes Classifier, Random forest, SVM, KNN, PCA, K-means, neural networks, regression, clustering etc)
- Deep Learning(CNN, RNN, TensorFlow, Keras,  CNN, RNN)
- Experience with version control systems (Git)
- MySQL, PostgreSQL
- Docker
Part-time of full time job with flexible working hours. Professional growth. Office near the metro station. Complex tasks. Small team. Ability to work remotely.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent

Build successfull data-driven product from scratch.
Fast learner, passionately love numbers.

Skills:
Statisctics
Machine learning
Python(NumPy, Pandas, Matplotlib, Scikit-learn)
Pyspark
AWS (Sagemaker, Athena)
Jupyter notebook
SQL (complex queries)
Linux(advanced user)
Web scraping (BeatifulSoup, Selenium)
Scrum
I am looking for an interesting job that will allow me to grow rapidly in the field.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper

Competition on Kaggle:
20/3,614 place  - ASHRAE - Great Energy Predictor III
23/1219 place - G2Net Gravitational Wave Detection 
1/37 place - Company Acceptance Prediction 
2/11 place -  INT20H Hackathon
3/11 place -  INT20H Hackathon

Master diploma: Speaker Recognition and Sentiment Analysis from Audio 
Bachelor diploma: Research universality of Transfer Learning in CV
Feb 2021 - Current time. Data scientist in Deloitte Ukraine
Finished - Computer vision (segmentation, object detection and classification) of BPMN
Active - NLP (keyword detection, summarization, classification) of sites
Active - MLOps SaaS platform (kubernetes, KubeFlow, AutoML engines)

Aug 2019 - Aug 2021. Data Scientist in HyperStarDev. 
Subject: Time series forecasting, clusterization, recommendation system, statistics
Tasks: built stable forecasting system and analysis of sales though serverless approach
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent


Ferrari Financial Services AG, Munich, Germany,
•	Risk Management & Compliance intern 
•	Supported for default management, control, risk and compliance activities within the company. 
•	Designed and programmed 5 VBA software units to be used by all the employees, directed on automaton of the procedures and human factor risks mitigation. 
•	Redesigned 3 procedures within the company for the process optimization purposes. 
•	Coordinated and described by flow charts most of the company processes. 
•	Analyzed data in the context of risk management.

Munich RE, Munich, Germany, 
Innovation and Project Management intern
•	Supported in marketing strategy development, market research, business planning in the scope of GDPR Compliance web project.
•	Brought new ideas into the development of the calculating logic for the GDPR Compliance web.
•	Received intensive SCRUM master trainings
•	Convinced the team to incorporate new features into the program.
•	Supported in ANGULAR programming.
•	Supported in development of the project planning.
 
Robert Bosch, Singapore,
Sales intern (Automotive Aftermarket)
•	Trained and improved efficiency of 4 new team members.
•	Initiated and conducted Power Generators market study.
•	Handled 12 Singapore customers, was responsible for purchase orders, price determination.
•	Developed databases and coordinated program-related projects towards customers.
•	Achieved constantly and helped team to exceed sales targets for Singapore by 155%: 
Planned sales versus actual sales for Singapore April-July 2015:  550,000 SGD: 850,000 SGD.
Position: Data Scientist
Category: Data Science
Experience: 10 years | English: fluent

- [Bank] Generated number of profitable short- and medium- term trading signals using various ML and AI techniques.
 - [Bank] Was leading algo-trading platform development.
 - [Bank] Played crucial role in replacing OneTick with KDB stack for whole bank, including multiple years of trade and quote data and huge amount of analytics.
 - [Bank] Designed and developed realtime reporting and monitoring portal for FX trading
 - [Luxoft] Created proof of concepts for financial sector
 - [Luxoft] Developed curriculum and was leading Junior Corporate Programme in Dnipro
FICC Trader | Investment Bank, Singapore
2018 - now

FX Trading, Director | Investment Bank, Singapore
2013 - 2018

Project Coordinator / Senior Software Engineer | Luxoft, Ukraine
2012 - 2013 

Software Engineer | EPAM, Ukraine 
2010 - 2012
Applying machine-learning and AI techniques to real world problems, preferably, but not limited to financial sector.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate

Alumni of the ProKG Mentorship Program. Mentored by Mr. C. Jumashukurov (Investor, MBA, Harvard Business School), March 2014 – September 2015;
 The winner of the internship program at Central Bank, Ankara, Turkey, July 2014.
FINANCIAL ANALYSIS CONSULTANT
JIA (BUSINESS ASSOCIATION)/TEXTILE AND TRANSPORT INDU.
January 2020 – present
Developed and upgraded financial reporting tools 
 Developed real-time (cloud-based) consolidated financial statements that helped CFO’s in decision making;
 Minimized financial reporting timelines up to 25% that increased productivity and decision-making speed;
 Developed the Balanced Scorecard, BSC that provided the CEO with real-time business intelligence.

INVESTMENT ANALYST		                                      HIGHLAND CAPITAL PRIVATE EQUITY & MEZZANINE FUND
September 2018 – December 2020		                      Conducted due diligences and developed financial models
 Completed due-diligences of three portfolio companies that led to investments worth of USD 3,4 mln;
 Saved over USD 1.2 mln. by making a deep analysis of a milk industry and showing prospective risks;
 Analyzed market data and developed financial models for prospective portfolio companies;
 Developed a financial model with valid projections that helped in decision making for investing USD 0.8 mln. in a portfolio company from a construction materials industry.

PROJECT ASSISTANT				      
HIGHLAND CAPITAL PRIVATE EQUITY & MEZZANINE FUND	
January 2016 – August 2018			      
Provided administrative and technical support
 Contributed administratively and technically to the launch of the first private equity investment fund in the Kyrgyz Republic with a portfolio worth USD 23 mln. (EBRD, IFC as institutional investors, and private investors); 
 Managed annual administrative budget worth of USD 25 000;
 Administered four events on the launch of the HC Fund and investment opportunities for SME; 
 Recruited initial team members: investment manager, office manager, accountant & managing partner assistant.

INTERN				                         	      
HIGHLAND CAPITAL PRIVATE EQUITY & MEZZANINE FUND
November 2015 – December 2015		                      
Assisted managers in covering daily operational needs
 Helped the Fund's CEO in analyzing financial models and collecting relevant market data;
 Conducted marketing researches in FMCG industry;
 Resolved administrative issues of the office.
Data Science Skills: Python, Tableau, Machine Learning and Ms.Excel. Capable of developing models that help sort and extract useful insights from complex data.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent


Finished Data Science course
by Main Academy association
There were several Data Science related projects done while taking course:
• Flat rent prices prediction machine learning model along with data collection (in that case – web scraping)
• Development of an algorithm for detecting similar topic for a news website.
• Informational dashboard describing market share of top 1000 Forbes companies.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Finished: Projector classic ML course. PhD in Chemistry

Finished Projects:
1) Predictions of scientific paper citation rate 
2) Environmental Sound Classification for very specific purpose
3) CNN for inverse problem solving for medical, industrial or scientific application

Projects include: 
1) Selenium and Python requests multi-thread web scraping (200k+ data points collected, more to go) 
2) Data treatment and visualization, EDA, baseline estimation
3) Numerical and categorical feature engineering using domain specific knowledges in chemistry and academical writing, basic text processing
4) Fine tuning of custom CNNs
6) Special purpose signal processing
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: intermediate


First Heartland Jusan Bank	Almaty, Kazakhstan
  Data Analyst                                                                                                                 November 2021 – Present

·	Monitoring the correct operation and maintenance of the automotive system;
·	Report automation and improvements, creating dashboards;
·	Uploading data for building a model;

·	Used technologies: PostgreSQL, SAP BI Launchpad, Microsoft Excel, Outlook, Jira

Freedom Finance bank                                                                                                   Almaty, Kazakhstan                         
  Data Analyst                                                                                                     	April 2021 - October 2021

·	Analyze and structure information, make objective decisions;
·	Automation of reporting, building dashboards;
·	Formation and provision of reports for top management, structural subdivisions, branch network of the bank;
·	Used technologies: Microsoft Excel, Microsoft Power BI, Outlook, Jira
Position: Data Scientist
Category: Python
Experience: 1 years | English: upper


First, I worked in the University Lab (Taras Shevchenko National University of Kyiv, Nuclear Spectroscopy laboratory) as a senior lab assistant. I was working on analyzing the dataflow taken from the Lumical calorimeter system at DUNE neutrino experiment. I used ROOT data analysis framework (C++) and Python data analysis libraries: numpy, matplotlib, scipy, pandas, and iminuit. The working process included data processing, data selection, statistical analysis, physics constraints optimization, and fitting. At the same time, I was working on my bachelor's thesis, which covers an analysis of rare physical processes at Belle II experiment (Japan). This job contained a lot of mathematical approaches such as Monte-Carlo simulations, using basf2 framework (python 3) and physical events' reconstruction. 
After successfully finishing the bachelor's program at TSNUK and enrolling in a master's degree at the same University I started to work on the Belle analysis. This work includes writing a Monte-Carlo code (Evtgen framework) for physics process event simulation and further processing them (reconstruction) in the frame of BASF (Belle Analysis Software) program. I have written a difficult object-oriented code using BASF libraries in C++ and used some well-known algorithms such as the depth-first search for increasing the performance of the program. All these steps also include writing shell scripts (mostly bash, sometimes csh) for automatizing and remote controlling the above-mentioned tasks. I've been working with Linux (Ubuntu, Mint, CentOS, Scientific Linux) for about 4 years, and in addition, also have a bit of background in crypto-oriented projects like testnets where I also got solid Linux experience. 
In a few months, I started my remote internship at the European Organization for Nuclear Research (CERN) where I work on performance studies and software profiling of FCCAnalyses framework proposed for solving data analysis problems in the prospective Future Circular Collider experiment. The framework is written in C++ under the hood, built on the functional programming paradigm, but uses a Python API for users to set parameters, configuration, and other physics properties to analyze. I had to use the profiling tools that allow CPU profiling of both JIT-ed, multithreaded C++, and Python codes. I worked with perf, cProfile, callgrind, gprof, and gperftools. In the meantime, I also worked in DESY on a data-analysis project in the frame of CMS experiment (C++).
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper

I graduated from the Robotdreams course "Profession Data Science" with the highest mark of 140 / 150. Also, I passed the test and joined the ML Google Bootcamp for Ukrainians.
Firstly, I worked a lot in a team. In university, I was head of the cultural commission. I carried out active work on the student organization of cultural events among students. Also, I worked as a brand ambassador and as an admin on the filming set. I carried about team workflow. 

Have a bachelor's degree in CS. As a Data Scientist, I studied several courses and did some projects. I`ve worked with such technologies as Docker, Tensorflow, Keras, Pandas, SQLite, Numpy, Mathplotlib, Seaborn, and Streamlit. I`ve made a Neural Network with Docker that predicts football player position. See my GitHub.

Highly-motivated Junior Data Scientist. Passionate about new technologies. Open to new knowledge. Ready for new challenges and fast studying.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


FivOne Education (9 months):
• Analyzed a bunch of information to create online/offline courses and marathons for wide ages (10 - 50 y.o.): "Introduction in Physics", "Python for games", "Introduction in Cybersecurity", "Introduction in Machine Learning", etc. 
• Successful worked in team and communicated with outsource lecturers.
• Analyzed statistics to create targeting advertising and to respond supply and demand.
Freelance (6 months):
• Analyzed scientific data for confirmation or refutation of different physics models.
• Visualized the results for representation to scientific mentors.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


For 1.5 years have worked as a data scientist in an automotive project. Built a system for road coverage quality prediction from vehicles' inertial sensors data. Also worked on the algorithm to estimate friction between vehicles' tires and surface of the road, which required a comprehensive EDA. Used AWS, libraries for data analysis (numpy, pandas, sklearn), data visualisation (matplotlib, seaborn, plotly), supervised learning tree-based algorithms (XGBoost, Random Forest), unsupervised learning dimensionality reduction (PCA, TSNE) and clusterisation (KMeans, DBSCAN) algorithms.
 
Separately, conducted research and experiments in computer vision and natural language processing fields:
CV: embryos quality image classification, face generation (VAE and GAN), real-time weapon detection (YOLOv8)
NLP: browser bug-reports classification (RNNs), question answering (LLMs and BERT-like models), invoice question answering (LLMs).
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper

I always try to focus on the business need and find the trade-off between the precision of the analysis and the value for business.
For 3.5 last years I work as data scientist analyzing mostly user data (gaming, telecom): general statistical analysis, building ML models, analyzing a\b tests on top of analysis\ predictions.

Before becoming a DS I spend 5 years in sociology\market research, mostly working with quantitative tasks (design and analysis of surveys).

Can share github profile and some articles (not research papers) on request.
- product company (not fintech, not gambling \ betting)
- possibility to contact directly with product \ marketing team or other internal customer for better implementation of ideas
- user behavior analysis as main part of work. Would be great to have also another tasks (text \ images \ geo processing, etc) - I do not have commercial experience with it, but I'd like to apply what I know and learn new things
- team of data scientist \ data engineers (not a single person in company)
- possibility to work remotely, at least part of the time, is a big advantage
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent

My last big project involved creating a system of sentiment analysis for Ukrainian and Russian language basically from nothing: I took part in designing the annotation guidelines and annotation processing, and then I have found the best tools for the job and built a good deep learning model which is now used in production.
For 3 years I have worked as data analyst in a think tank (working with datasets concerning economy and society in Ukraine and other countries).
After completing Data Science Summer School in Lviv and intensive 3-month Natural Language Processing (NLP) course from Projector, I started working as data scientist in a small company called Semantrum. My job included managing the process of annotating the data, cleaning and preprocessing the data, desigining and training machine learning models for different NLP tasks (named entity recognition, topic classification, clustering, sentiment analysis etc.). The primary tools I used were pandas, spacy, scikit-learn, keras and pytorch.
I would like to continue working in data science, especially (but not necessarily) if the work will contain elements from NLP and deep learning.
I am an open-minded person willing to try and learn new things, so I don't have particularly strong expectations towards the company. I believe that any type of company can be a good fit for me, if there are some interesting tasks and some professional people on the project.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


For a half of year I have worked on large retailer from US. 
My job consisted of cleaning up the data, creating new features, training models and evaluating performance. The dataset was quite large (8 million rows and 25 thousands columns), so it was a big data project. 

Programming language: Python, SQL.
Used frameworks: 
Visualization & Preprocessing: Pandas, Numpy, Matplotlib, Seaborn, PyAthena, boto3, PySpark. 
Machine Learning: Lightgbm, Tensorflow, Scikit-learn. 
AWS Services: Athena, EMR, Sagemaker, S3. 


For another half of a year I have worked on large advertiser also from US
Overall that was probably more the job of Data Engineer rather than Data Scientist, as mostly my responsibilities consisted of sending the data to different partners, creation of different reports, analyzing the data 

Programming language: Python, SQL, Bash.
Used frameworks: 
Preprocessing & other: Internally developed frameworks, boto3, Selenium, Jenkins. 
AWS Services: EC2, Athena, S3, Data Pipelines.