lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Python developer

Designed dashboard for BP private monitoring platform - Palantir consisting of:

- developing a python algorithm that recognizes pressure anomaly patterns in real time with 92% accuracy
- it allows simultaneous, real-time identification of pressure anomalies in 100+ oil and gas platforms without direct well intervention
- a web-based user interface for real-time monitoring of well conditions
parameters extractions from BP well database and data management using PostgreSQL
optimized algorithm - reduction of running time by 70% while maintaining high accuracy


Database developer assistant

- Cleaned and integrated 500+ GB of numerical data, 1470 image data, and 744 document files
- Establishment of a well-sorted and fully standardized core database using SQL Server Management Studio Designed a web page outline that provides users with multiple functionalities such as smart search, multi-filtering, visualization
- Web-based database design and construction using Python (Django), JS, Ajax, HTML, SQL

Projects:

Customer Analysis

- Performed dimensionality reduction using principal component analysis respecting trade-off between parsimony and the amount of variation in the data
- Used a hierarchical, followed by non-hierarchical clustering techniques combination on newly discovered variables
- Interpretation of principal components loadings and clusters for a better understanding of customer segments

Games recommendation system

- Researched about drawbacks of traditional collaborative and content based approaches in recommender systems
- Built a 2 layer Machine learning system comprising of LightFM for user generation and gradient boosted decision tree for user ranging
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: upper

Projects:
text classification for an education platform
Video classification for game understanding
BERT for a contextual translation
Text-to-Speech 
Restaurant menu processing
Speech recognition
Discount prediction
Podcast-to-Summary using ChatGPT
Python for Data Science and basic web development
Keras & PyTorch
Sklearn
Pandas
LGBM
Transformers
Position: Data Scientist
Category: Python
Experience: 2 years | English: fluent

Fluent English. Excellent soft skills, team player.
Currently working for Yandex (4th largest search engine worldwide), dealing with 20 TB of data per day.
Interested in Data Analysis, Machine Learning, Artificial Intelligence, Data Mining.
Python, MapReduce, SQL, Linux, Data Analysis, Machine Learning
I'm open to any offers.
Position: Data Scientist
Category: Other
Experience: 0.5 years | English: fluent

Performing role of Data and Business Analyst, our team implemented machine learning algorithms which allowed business significantly enlarge the reach of users for advertising. I implemented corresponding metrics to evaluate efficiency of production algorithms (Precision, Recall, F1-measure, Confusion Matrix, etc).
- python
- pandas
- numpy
- matplotlib
- machine learning
- AWS
- Linux
- English (upper-intermediate)
- Apache Spark (pySpark)
Preferably advertising, eCommerce, similar.
Not banking, healthcare, etc
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

1)	12.2017 – 01.2018 Vodafone BigData Hackathon (+ acceleration program)
2)	Our team won the first place in Business Intelligence Hackathon 10.2017 with NLP model
3)	Participating Kaggle competitions(Web Traffic Time Series Forecasting( Forecast future traffic to Wikipedia pages), FIFA UT (short-term))
4)	Coursera Basic Statistics( University of Amsterdam)
5)	Coursera Introduction to Data Science in Python
6)	Course from Open Data “Practical Machine learning with R”
7)	Course “Introduction to Data Science, Business Analytics, Big Data and Artificial Intelligence(Oleksandr Romanenko)”
Python: Pandas, Numpy, Scipy, statsmodel, FB Prophet, XGBoost, plotly
Databases: PostgreSQL, My SQL, Oracle, MS SQL, familiar with NoSQL
Additional tools: Tableau, Oracle BI

Work experience
1.	User clusterization(K-means) for more efficient bonus program
2.	Cohort analysis, customer retention modeling
3.	Profit forecast(regression, fb prophet, SARIMA)
4.	Data cleaning, aggregation and visualization with Python (Pyodbc, Pandas, Numpy, matplotlib, plotly) and Tableau. 
5.	Aggregating and synthesizing data from various structured and unstructured data sources (My SQL, T-SQL, Postgresql, JSON).
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper

Enjoyed studying advanced statistics course and understanding of probability theory as well machine learning techniques in order to improve performance metrics.
- Python, pandas, sklearn, XGBoost and data analysis tools.
- Advanced regression techniques.
- Computer vision object detection with Tensorflow Keras. 
- Studied advanced statistics and machine learning course as well completed courses for Python Pandas and machine learning.
- Python Django framework.
- Data mining with python Beautiful Soup library.
- Finishing Data Science Master`s degree in European University. (Final Master thesis only left).
It would be interesting for me in Finance / Infrastructure/ Construction / Healthcare / Sport, but always open to consider any promising or interesting projects.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


Python Programming:
Proficient in Python programming language with experience in developing various applications and projects.
Knowledge of Python's core concepts, data structures, and object-oriented programming (OOP) principles.
Experienced in using Python libraries and frameworks to build efficient and scalable solutions.
OpenCV Project:
Developed an advanced computer vision project using OpenCV, a popular Python library for computer vision tasks.
I'm eager to work on AI/Ml projects, creating smart systems that can learn and adapt. My goal is to apply AI/ML to solve real-world problems and continue growing in this exciting field.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: intermediate


Python, scikit-learn, numpy, pandas, MySQL

I have passed courses on Kaggle(topic learn); ML on Prometheus

Also I have experiance as a mathematican(solving different tasks for students) and took part as volunteer on dev. events. This year I`ll attend to IForum as volunteer too.
Best regards:)
I would like to get position where I`ll grow up as a specialist.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper

ACM ICPC (International Collegiate Programming Contest) 1/8, 1/4, 1/2 participant and winner in different years.
Python, SQL, pandas, Java, kotlin, C/C++, math statistics, computer algebra, mathematical physics, computational mathematics, factor analysis, cluster analysis, econometrics, Matlab
Challenging tasks and growing
Position: Data Scientist
Category: Python
Experience: 0.5 years | English: upper

Full implementations of neural network with gradient decent optimizer from scratch, using python numpy.
Currently working as deep learning developer.
Implementation other algorithms of machine learning/statistics/data-mining  such as:
- linear/polinomial regresson (python,numpy,matplolib).
- a-priory  algorithm (python numpy)
- k-measn with mean shift optimization (scikit-learn)
- k-nn (java)
- brutforce (c++)
- chat app (java)
Python
TensorFlow,TensorFlow Serving 
Docker 
PL/SQL,MS SQL 
Scikit, numpy, matplotlib, pandas  
Java core
RSA encryption
json, REST, SOAP
C++ 11
Linux, bash
jupyter notebook
Hadoop environment basic
http, css
Im extremely obsessed with data scenes. Especially applying various approaches(algorithms) for different statistical/regression/classification problems.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: intermediate


Real Time Cryptocurrency trading bot
• Got the strategy of when to buy and when to sell the special cryptocurrency which was written in R programming language, I transfered it into
Python programming language
• Backtestedandsimulatedthestrategywithfakemoneywiththepricehistoryofcryptoinordertoevaluatetheperformanceofstrategyusing
Python (Zipline package)
• Deployedintorealtimetradingbotusingweb‐socketforgettingdataevery5minutesandusedBinanceAPIforbuyingandselling
• UsedMath,ScipyandNumpypackagesforsomecalculations
Telegram bot for Uzbekistan Railways
• Deployedtelegrambotwherecustomerscanfindanswerstofrequentlyaskedquestionslike(Howtobuyorreturnticket
• UsedPython(Aiogram,Asyncio)
Features to Musaffa.com website
• Musaffa.comisawebsitewhereonecangetinformationaboutstocksandknowwhetherit’sHalaltoinvestornot
• WroteformulasinPythonforInvestor‐CheklistpartofMusaffa.com
• 4formulas”ExpectedAnnualReturn”,”ModerateRisk”,”SharpeRatio”,”DividendYield”iscalculatedandsavingdatainFirebase
• WroteformulasinPythonforForecastCollectionpartinMusaffa.com
• 3formulas”Price”,”Revenuepershare”,”EarningsPerShare”iscalculatedandsavingdatainFirebase
• BuilddockerwithDevOpsengineerinordertoruneveryformulaonceinonedayandupdateallinformationinFirebase
Researches on Blockchain
• MaderesearchesonBlockchaintechnology
• Mostoftheresearchesweredoneondeployingsmartcontracts
• Searchedforquestionshowtheblockchaintechnologyworks.practisedSolidityprogramminglanguagefordeployment
Researches on Trading strategies
• Havedoneresearchesonreal‐timetradingwithstocks.
• Havetestedandsimulateddifferentstrategiesonhistoricalpricesofstocks
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper


Recently Completed Projects:
1. Armenian-based bank - The project was about a loan default prediction in the bank. This project's goal was to build a machine learning model that can predict if a person will default on the loan based on it and the personal information provided. The model was intended to be used as a tool for making decisions on issuing loans so that the risk can be lowered and the profit can be maximized. There were different functionalities from data gathering from different sources to training various models. Finally, a Gradient Boosting model was built to predict loans' probability of default. The working process involved a lot of communication with business owners, retail banking colleagues, planning, and development.
Languages: Python, SQL
Environments: PyCharm IDE, Libs: NumPy, Pandas, Scikit-Learn, Jupyter Notebook
Position: ML Engineer

2. US-based information technology company - In this machine learning project, open-source datasets that are publicly available were taken, and various methods/techniques of performing time series forecasting were discussed. The project aimed to research and develop several ML models to help the traditional methods such as the holt-winters method, autoregressive integrated moving average method, exponential smoothing methods which were discussed and avoided for Time Series Prediction with data preprocessing tools.
Languages: Python
Environments: PyCharm IDE, Libs: NumPy, Pandas, Scikit-Learn, Jupyter Notebook
Position: AI/ML Engineer

3. Germany-based biopharmaceutical industry - The project was about building a solution which will search necessary ontologies in a database of public articles and generate results as an outcome of findings. There were several assumptions agreed upon regarding the project.
Languages: Python, SQL
Environments: PyCharm IDE, Libs: NumPy, Pandas, Scikit-Learn, FuzzyWuzzy, Spacy, Dask Jupyter Notebook
Position: ML Engineer

4. International financial institution - In this Data Analytics project, the company sought to determine likely outcomes by detecting tendencies in descriptive and diagnostic analyses. We found descriptive analytics to be insufficient for informed, data-driven decision making. As such, diagnostic and predictive analytics are increasingly important to organizations.
Languages: R, Python, SQL
Environments: PyCharm IDE, Jupyter Notebook, Python Libs: NumPy, Pandas, Scikit-Learn, R libs: dplyr, tibble, ggplot2
Position: Data Analyst
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper


Recently, I have completed ML in Production and NLP Beginning courses at Projector, expanding my knowledge of the machine learning model lifecycle, from data handling and training to deployment, monitoring, and automatic updates in production. Through these courses, I gained hands-on experience in building and deploying my machine learning models. Notably, during the NLP course, I developed a Telegram chatbot for a charitable organization.

Before taking maternity leave, I gained experience as a Data Scientist in a Telecom company, where I used Python to train predictive models and improve profitability, growth, and other KPIs. I also developed client segmentation models and implemented predictive models on SQL, and conducted A/B testing to evaluate model performance in production. 
Additionally, I worked as a Quantitative Developer and I implemented financial algorithms using C++/C# programming languages and applied automatic differentiation to solve financial problems. I also integrated AD with financial libraries and created comprehensive methodology, implementation, and validation documentation.
I hold an MS in Systems and Methods of Decision-Making from NTUU "KPI" ESC "IASA".
I am eager to take on new challenges and continue growing professionally.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper

Successfull completeness of different Data Science courses and internships. Effective models development for making decisions on lending. Prosperous creation of a eKYC (online customer verification) product part
Reports building and validation; forecasts creation using time series analysis in combination with ML methods; credit models creation, validation and support in FinTech company; computer vision and NLP projects in KYC product.

Stack: Python, SQL, Git, AWS, Docker, Linux, PyCharm, Jupyter, Google Colab
Respect to employees and competent work conditions
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: upper

I have a degree of Software Engineer with 5 years’ experience of software development.

My experience include reports generation and creating dashboards for Ambulance, collecting and processing sensitive data, machine learning, recommendation system, scraping data from network, data mining and visualization.

In my opinion, communication and ability to delivery result is very important for business performance, as well as quality of technical solution.
reports generation, dashboards, collecting and processing sensitive data, machine learning, recommendation system, scraping data from network, data mining and visualization, PostgreSQL, PHP, MySQL, Unix, JavaScript, SQL
Interesting and complex task.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: intermediate


Requirements analysis;
Working with database, data collection and preparation;
ML models building, evaluating and maintenance;
Classification, regression tasks;
Using methods as boosting trees, random forest, linear models;
Deploying online and offline models, API development;
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: intermediate

Speaker on local DS courses for students.
•	Research and Development of solution architecture for object detection (keras, azure)
•	Research and Development solution for semantic segmentation (pytorch).
•	Research and Development solution for demand forecast based on time series (R, XGBoost/LightGBM, DHC)
•	Research and Development solutions for people tracking and counting, indoor and outdoor (keras, face identification)
•	Research and Development solution for analysis questionnaire of values (Word2Vec/BERT, CoreNLP, sentiment analysis)
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


- Research existing ML/AI algorithms and best practices in the field
- Read / interpret and implement scientific papers
- Apply mathematical and statistical theories and techniques to solve
problems
- Build / implement predictive models and machine-learning / AI algorithms
- Modify and combine different models through ensemble modeling
- Process, clean and store data
- Perform preprocessing and analysis of structured and unstructured data
- Identify data patterns and trends
- Propose solutions and strategies to existing challenges
- Present information using data visualization techniques and dashboards
- Document all processes and codes
- Collaborate with the IT team, partners and the project manager to meet
project goals
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


Research Internship (6 months) with a topic of 3D Pose Estimation using GAN Neural Networks

11.2022 - currently
Data Scientist working with mostly CV related tasks such as segmentation, classification and multimodal tasks (textual image description). Other DS related tasks such as analyzing the data scraped from the internet.
Technology stack used:
Python, Keras, PyTorch, Tensorflow, Tensorboard, MLflow, opencv
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent


Result-driven Data Scientist. My areas of expertise include business analytics, machine learning, deep learning, and cloud computing. Experienced working with large datasets and deriving insights from data, developing algorithms for statistical and mathematical modeling, and building machine learning models that drive business decisions.

Worked on several projects using Python and Machine Learning techniques like Clustering, Regression, and Natural Language Processing (NLP). Knowledgeable in Python, JavaScript, and libraries like Pandas, Numpy, Matplotlib, Plotly, Scikit Learn, TensorFlow, NLTK, VADER, etc. My main goal is to solve problems using data.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


- Result-oriented Data Scientist with a strong database background, offering a blend of data analysis, machine learning, and data management skills. Experienced in optimizing SQL queries, developing ETL pipelines, and utilizing advanced statistical models for predictive analytics.
- Proficient in using Python libraries and NLP for data processing and uncovering hidden patterns. Skilled in the administration and effective utilization of databases such as PostgreSQL and MongoDB, coupled with a strong knowledge of Power BI for data visualization. Demonstrated success in providing data-driven solutions that facilitate strategic decisions and improve overall business performance
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: intermediate

Master's Degree in Computer Science
Retail:
Uplift, Look-alike modeling, and ranking for promo campaigns. 
Python, MS SQL. ML and statistical frameworks/libraries.

Ranking:
finding similarities between the candidate's profiles and job descriptions.
Python, MS SQL. ML and statistical frameworks/libraries.

Betting:
approximation and probabilistic models for sports events, data parsing
Python. ML and statistical frameworks/libraries.

Trading:
technical indicators and Flask API development. 
Python, Docker, MySql. ML and statistical frameworks/libraries.

Summary:
Data preprocessing, analysis, and feature engineering.
Have experience in classification, regression, ranking, NLP, and uplift tasks. Flask API development.
No gambling, please
Position: Data Scientist
Category: Python
Experience: 1.5 years | English: fluent


Risk Analyst | MaxDecisions Inc., USA January 2022 – May 2022:
(Data Science / Risk Management)
• Prepared the dataset for machine learning models by overviewing Weight of Evidence (WoE), scaling non-categorical variables, and oversampling the data to address class imbalance.
• Implemented ML algorithms including SVM, XGBoost, and DL to predict Probability of Default for clients.
• Compared the performance of the models using metrics such as K-S scores, ROC curves, and confusion matrices on the test and validation datasets, and produced rank order tables to evaluate the models' effectiveness.
• Collaborated effectively with other team members and stakeholders, including data scientists, engineers, and business leaders, to deliver high-quality risk management solutions to clients. [Presentation], [GitHub]
• Tech stack: Python, Scikit-Learn, TensorFlow, Keras

Senior Year Project Engineer | Arcelik Inc., Turkey October 2019 – June 2020:
(Project Management / Strategic Planning)
• Led a warehouse improvement project that involved relocating departments to optimize flow value and increase capacity by 2800 ft2, using MATLAB to assess and visualize the changes.
• Improved logistics efficiency by optimizing the path for forklift trucks, reducing wait time by 20% and enhancing productivity.
• Boosted revenue by 10% by designing and implementing wedges for coil steels, reducing damage and waste.
• Authored a comprehensive 40-page academic report detailing the project methodology, results, and recommendations for future improvements with a team of seven. [Presentation], [Report]
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


- Risk prediction and financial performance prediction models from concept, data exploration, through feature extraction, model training and model performance assessment
- NLP tasks like entity extraction, summarization
- integration of ChatGPT
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper

FS project: develop algorithm for computing short-term sales forecast
CPS project: compare 2 new data collection approaches, develop technique for merging data retrieved by the approaches
SSCA project: develop algorithm for choosing similar available data source, which will replace data from lost one
R, Python, Math statistics
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

- Masters degree in advanced geostatistics and modeling from University of Alberta, Canada
- Nano Degree in Data Analytics, Udacity
- Machine learning Engineer Nano Degree, Udacity
- Successfully delivered 3 data analytics projects in USA and Canada.
R, Python, SQL, Machine learning, Data science, Random forest, Tableau,  Numpy,  Pandas, Sklearn, MATPLOTLIB
Position: Data Scientist
Category: Data Science
Experience: 9 years | English: upper

6+ years as a lead data scientist in the company providing analytical solutions for fintech and companies all over the world. Built a lot of models, communicated with developers, business customers and all stakeholders.
R,  Python,  SQL,  MatLab,  C/C++, Spark,  Machine Learning.

data preparation (intensive work with databases, XML, RegExp), 
preprocessing incomplete and incorrect data, 
Big Data processing (using Spark), work with AWS services,
supervised models building - linear and logistic regression, XGBoost, SVM, random forest etc., ensembles of models, 
unsupervised models building - clustering techniques etc.,
text retrieval and natural language processing basics,
image recognition basics,
ranking problem,
features generation and dimensionality reduction, 
exploratory data analysis and statistics (confidence intervals, hypothesis testing, variables significance),
building credit risk and fraud detection models, 
performance analysis (AUC, confusion matrix, generalization issues etc.)
Building models based on machine learning techniques, interesting tasks, not just statistical analysis. Willing to learn something new.
Position: Data Scientist
Category: Other
Experience: 1.5 years | English: fluent

Participated in numerous projects in fintech industry
R,  Python,  SQL,  Matlab,  machine learning,  data mining,  data visualization,  algorithms,  Excel, data analysis, statistics, text mining
Professional development, convenient office location