lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper

Prepared a course of lectures in Statistics and Data Science for company members on descriptive statistics, distributions, hypothesis testing, and R tools for data visualization.

Created a pipeline for monitoring key product metrics on the dashboard shared with all company members.

Personally prepared two releases of big Ruby on Rails application, including detailed test coverage on Rspec/Capybara and Gherkin.
Data Scientist with hands-on experience in Ranking Systems, Data Analysis, Computer Vision (Image Matting and Segmentation problems) and Natural Language Processing (Social Accounts Categorization, Term Extraction). For the purposes of these projects, I used PageRank algorithms to get social graphs for further ranking and trained ResNet, TFIDF, Logistic Regression, and Random Forest models.

Experienced Full Stack Ruby on Rails Engineer in the pharmaceutical industry. Developed and tested Rails+React applications with IDE and version control for clinical data management and standardization.
I am looking for a Machine Learning project in CV, NLP or Recommendation/Ranking system domains. Interested in both research and engineering parts.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent


Data Scientist with hands-on experience utilizing statistical modeling and machine learning techniques.Background in data processing and building predictive models that translate data points into business insights.
Position: Data Scientist
Category: Python
Experience: 3 years | English: fluent

Kaggle MNIST competition (98.6% accuracy)
3y experience in Web Scraping and imitation of user behaviour in well protected systems, data managment and analysis
Data Scientist with huge experience of scraping well-protected systems, user behavior imitation and cybersecurity background. 
As Data Scientist I have strong analytical skills and experience of building ML & DL models, tested on Kaggle competitions. Hypotesis testing and visualization skills gained with huge experience of data analysis in physics and biology.  

Experience:
- MNIST (Kaggle competittion): classifier of numbers from 1 to 10 with using anomaly detection, strong data analysis and CNN (98.7% accuracy for CNN, ~92% for MLP+PCA)
- Fashion MNIST: classifier of clothes' types with classical machine learning methods: CVM, Decision Tree, Linear Classifier, XGBoost. Just for fun, state-of-art is CNN architecture (accuracy 90.8%)
- Captcha generator: example of my work with image libraries
I'm passionate with Computer Vision and Generative AI, Data Analysis and Web Scraping
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

Commercial experience:
-Took part in Developing PostgreSQL and MongoDB application for high speed access to large volumes of data. 
-Successfully developed Recommendation System for application with active users. 
-Fully configured and managed PostgreSQL DB with PostGIS extension for team of Data Scientists with all its ETL processes. 
-Successfully automatized and scheduled lots of data gathering, processing and report making processes.
-Successfully developed model for product recommendations based on real customer data.
-Successfully developed Time-Series based recommendations based on real customer data.


Before commercial experience:
Many interesting pet-projects, including NLP chatbot, Emotion recognition system and etc.
Data Scientist with more than 3 years of commercial experience. 
Have solid experience with SQL databases.
DB infrastructure set up, DB Engineering, DB management, ETL processes optimization. 
Experience with NoSQL databases MongoDB and Redis.
Solid experience with AWS: AWS Lambda, AWS EC2, AWS  SageMaker, AWS RDS, AWS Redshift.

Solid ML experience.
ML model development and enhancement.
Product recommendations model development based on real customer data, Time-Series recommendations, ensemple methods, three-based methods, XGBoost, CatBoost, Statistical analysis, Images processing: OpenCV, Tensorflow, Pytorch, DNN, CNN.
NLP - Key-words analysis, Sentiment analysis, Word Embeddings, Ngram, RNN, LSTM, Attention.
Team work, interesting projects, opportunity to communicate with team and clients.
Position: Data Scientist
Category: Data Science
Experience: 6 years | English: upper


Data Scientist with over six years of experience in the field. I have strong knowledge and practical experience in computer vision and image preprocessing using opencv, as well as a solid foundation in math, statistics, and a variety of machine learning algorithms, techniques, and methods. 

I have experience with programming languages Python, also used С/С++, and Google Script, as well as with data science tools like NumPy, Pandas, Scikit-learn, OpenCV, Tensorflow/Keras, pytorch, lightGBM, and nltk. 

I have worked on various projects, including style transfer, feed algorithms, traffic forecasts, deep learning autocomplete, and item-based recommendations. 

Hold a master's degree in the bioinformatics field of research. Also I am a teacher of Data Science at  GoIT. My responsibilities in these roles included providing lectures for students, creating educational materials, making practical workshops for students, and measuring student achievements.
I'm a dedicated team player who thrives on collaborating with other skilled engineers to tackle challenging tasks and push the boundaries of what we can achieve. Learning new technologies and exploring innovative models is a passion of mine, and I'm eager to bring my expertise and enthusiasm to future projects. Together, I believe we can achieve great things and make a meaningful impact in the world.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper

Data Science Bootcamp

 - The 12-week Data Science Bootcamp program is designed to
demonstrate the world of Statistics, Data Analytics, and Data Science methodologies using R, Python, Spark, Spark SQL, Spark
Mllib, AWS, Hadoop,
Data Scientist with Programming background. Skilled in Python, R, SQL, statistics on large datasets. 
Extensive knowledge of data visualization techniques and visual design concepts. Dig in by extracting data and performing segmentation and statistical analyses on large population datasets (using languages such as SPSS, R, Python, SQL, Big Data). 

Image classification with Python (2022)
Given the Image Classification dataset consists of 6 classes, I am asked to build a model
that can correctly classify images. I applied a method called transfer learning and tried
three neural networks architectures: VGG16,Resnet50 and Inception-v3 Build a neural model that can classify with 92% accuracy.

 NLP with R(Keras) (2022)
I am provided with data containing public comments from social platform .I have been
asked to classify toxicity level of comments. I used tokenization method to prepare
comments for models. Build my model using Google BERT Algorithm and Keras library.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


Data scientist with specialization in data mining, processing, and building machine learning models to solve data challenges and inform strategic business decisions.
I have experience with projects involving:
- Fraud detection.
- Sentiment Analysis (NLP).
- Customer Segmentation.
- Customer Churn prediction.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: fluent


Data Scientist with work experience in Telecom and Banking industries.
Familiar with most of the popular data processing, visualization and modeling libraries.
- pandas, numpy
- seaborn, plotly, matplotlib etc.
- sklrean, prophet, scipy
- SQL
- Flask
- Docker

Worked with structured data and unstructured data.
- Customer data from telecom and banking industry for customer segmentations, ASPU prediction
- Timeseries analysis of ATM withdrawals and forecasting.
- Computer vision ( Face detection, Face recognition, OCR like Tesseract)
- NLP tasks ( Classification of survery results )
Looking to work in team with Senior/ more experienced Data Scientist so I can learn from them.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


Data Scientist
XYZ Corporation
June 2018 - March 2023

As a data scientist at XYZ Corporation, I played a key role in leveraging data-driven insights to drive strategic decision-making and optimize business processes. My responsibilities included:

Data Analysis and Visualization:

Utilized Python and R programming to analyze large datasets and derive meaningful insights.
Conducted exploratory data analysis (EDA) to identify patterns, trends, and outliers, and presented findings to cross-functional teams.
Created interactive visualizations using Tableau and Power BI to effectively communicate complex data to stakeholders.
Machine Learning and Model Development:

Developed and deployed machine learning models for predictive analytics, including linear regression, decision trees, and random forests.
Utilized data preprocessing techniques such as feature engineering, data imputation, and scaling to enhance model performance.
Conducted A/B testing and model evaluation to continuously optimize model accuracy and performance.
Data-driven Decision Making:

Collaborated with cross-functional teams to identify business problems and formulated data-driven solutions to improve operational efficiency and customer experience.
Conducted market research and utilized statistical techniques to identify opportunities and risks in the market, which resulted in strategic business decisions.
Presented insights and recommendations to senior management and stakeholders to drive data-driven decision-making processes.
Data Visualization and Reporting:

Developed and maintained dashboards and reports for monitoring key performance indicators (KPIs) and business metrics using data visualization tools such as Tableau and Power BI.
Created automated reporting processes to ensure timely delivery of insights and recommendations to stakeholders.
Collaborated with business partners to define reporting requirements and deliver actionable insights to drive business outcomes.
Collaboration and Teamwork:

Worked closely with cross-functional teams, including business analysts, software engineers, and data engineers, to collect and analyze data, develop models, and implement solutions.
Participated in regular team meetings and collaborated with colleagues to share knowledge, best practices, and insights.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


Data Scientist | YerevaNN Research Lab | Data Scientist
Projects:
• Learning representations of the chemical properties of Molecules:
– State-of-the-art in 8 prediction tasks out of 12,
– Advanced language models were applied, such as BART,
– Multiple biochemical datasets considered,
– Interpretability: predict toxic or soluble parts of the molecules,
– produce ZINC, USPTO and MoleculeNet datasets overlapping,
– preprint is available in arXiv:2211.16349.
• Heart arrhythmia (Brugada) detection from ECG
– ECG data is large, but the number of people is limited.
– Use invariant representations to remove patient-specific informa-
tion from the ECG and leave only essential information for disease
prediction.
– This method outperformed state-of-the-art methods on the ECG
data.
• Current project: Predict modifications of the given molecule, which
enhances the certain chemical property. Approach to drug discovery.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent

Selected Projects
•	Language and gender classification of named entities within business sites location names to support corporate social responsibility (NLP).
•	Developed an end-to-end machine learning solution for the prediction of weather changes in Australia.
•	Multi-label classification of Prose Review using NLP (NLP project)
•	Development of data pipeline from AWS s3 buckets/Azure blob storage to Snowflake WH for reporting.
•	 Applied ML classification techniques in investigating and analyzing current CO2 abatement technologies. 
•	Development of Interactive dashboards in Power BI for business intelligence and reporting to stakeholders.
Data & Systems Scientist/Engineer, Department of Jobs, Precinct & Regions, Melbourne, VIC. (Nov 2021 – to date)
•	Performed data wrangling, profiling and analysis on new datasets ingested from source systems using cloud-native tools.
•	Time series data analysis, modelling and forecasting for business case development and operations capacity scoping.
•	Process data modelling through optimized ML model selection, development, and evaluation to identify optimized parameters for process operations input. 
•	Developing PowerBI dashboards for operational reporting to leadership team and different stakeholders.
•	Built and developed optimized data models to suite business requirements and provided operational support of Data Warehouse and related data analytics systems in development and production environments.
•	Designed and built data pipelines for data structures involving data extraction, transformation, metadata, schemas and workload management.
•	Enhanced and optimize existing data ingestion, transformation, and extraction pipelines built for reporting and analytics on big data and EDW platforms.
•	Report generation and documentation of ML workflow for communication with internal and external stakeholders.

Selected Projects
•	Language and gender classification of named entities within business sites location names to support corporate social responsibility (NLP).
•	Developed an end-to-end machine learning solution for the prediction of weather changes in Australia.
•	Multi-label classification of Prose Review using NLP (NLP project)
•	Development of data pipeline from AWS s3 buckets/Azure blob storage to Snowflake WH for reporting.
•	 Applied ML classification techniques in investigating and analyzing current CO2 abatement technologies. 
•	Development of Interactive dashboards in Power BI for business intelligence and reporting to stakeholders.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper


December 2017–Present: Junior Data Scientist in Credit Suisse,
Created and presented models for manual process automatization
Provided short learning sessions for employees in R and Python Build a custom word embedding model for specific company needs.

September 2017–November 2017: Internship in Credit Suisse,
Done data manipulations and analysis for reporting needs

July 2017–August 2017: Internship in Nanores
Projecting nano-structures in Lumerical FDTD Solutions
Testing and parametrization of models, analysis of their results
Position: Data Scientist
Category: Python
Experience: 3 years | English: upper


Decision Making with analysis of data, managing and sharing of tasks with team workers. Investigating new ML algorithms and approaches to current models. Deployment of Collection model, Income estimation model, Limit Model, IFRS PD model with support of DataIku.  
Programming skills:
1. R
2. Python
3. Oracle SQL
4. DataIku
I would not prefer to work under mental and physical pressure.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent

Developed a multilingual OCR system to outperform Tesseract, achieving a 20% error reduction.
Improved performance for Heart-rate monitoring from video using Transformers by 10% over SOTA solutions.
Using Transformers for developing a time-series analysis for credit scoring decreased the number of incorrect classifications by 30%, saving the company more than 100k USD.
Dedicated and results-driven Data Scientist with 5 years of experience in creating advanced solutions for computer vision, data analysis, and natural language processing. Proficient in various programming languages and frameworks including Python, PyTorch, TensorFlow, Java, and C++. Strong expertise in developing and deploying machine learning models for real-world applications. Skilled in data analysis, pipeline optimization, and open-source technologies.
To leverage my 5 years of experience to continue advancing the field of machine learning. I aim to contribute my expertise in creating and deploying machine learning models for real-world applications, while continually exploring innovative approaches and technologies. Through collaboration with multidisciplinary teams and a commitment to continuous learning, I strive to drive impactful solutions that push the boundaries of data science and contribute to the growth and success of cutting-edge projects and organizations.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent


Dedicated and technically skilled business professional with a highly versatile skill set developed through experience and education. 

Self-motivated individual who is willing to invest time and energy to obtain in-demand skills. 

Proficient in data analytics and statistics. Professional use of Excel, Phyton, R, and Power Bi, tools.

Risk models apply analytics with a statistics-oriented approach.
Position: Data Scientist
Category: Project Manager
Experience: 10 years | English: fluent


Dedicated Maintenance Supervisor offering 19 years of successful team management in maintenance­driven roles. Adept at scheduling facilities maintenance to minimizing downtime and safety hazards. Well-versed in equipment troubleshooting and repair with focus on quality and efficiency. A certified Project Management Professional (PMP)® and a certified Google Project Manager. Committed to safety and efficiency with focus on providing teams with support and leadership to achieve goals. Skilled in minimizing production downtime via proper scheduling, inspection and troubleshooting. Proven history of expertise in identification and elimination of safety hazards. A Certified Google Data Analyst with expertise in Data Science/analysis Machine Learning, and visualization using R and Python Programming.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent

Associate Professor of Mathematics with more than 30 scientific articles. Successfully presented thesis “Differential equations with mixed fractional derivative”.
Deep knowledge of Financial Mathematics, Probability Theory and Mathematical Statistics. Actively developing skills in Data Science and looking forward to continuing my career in this field.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent

* 8 peer-reviewed journal articles in high-energy physics
* 4 conference talks, multiple posters presented
## Deep Learning for tabular data

* deep learning and classical machine learning approaches on tabular data for monthly revenue predictions, estimation  of payment probabilities, client and portfolio scoring models
* work with **SQL databases** including data cleaning with tools for distributed computing (such as `dask`), exploratory data analysis, hypothesis testing and model selection (using tools such as `ray`)
* **time-series modeling** for history-aware deal-by-deal revenue prediction
  
## Natural language processing (NLP)

* chat- and voice- bot models
* named-entity recognition for chatbots with transformers in English and Asian languages

## Other

* Voicebot, Speech-To-Text and Text-To-Speach web services
* Google Cloud services
* research-oriented tasks (more science, less engineering)
* flexible schedule
Position: Data Scientist
Category: SQL
Experience: 1.5 years | English: upper


Demand Intelligance platform

Service for prediction of city/area load based on historical data and events taking place in the city.

Technologies:
Python, TensorFlow, Keras, Pandas, NumPy, Time series forecasting models.

Genie Words Ads Generator
AI algorithm to generate contextual selling adverising headlines for texts from websites and implement description generation. Create the system for keywords detection and generated text rephrasing.

Technologies:
Python, Regular expressions, Spacy, NLTK, Markovify, Fuzzy Logic, Unsupervised Models, TensorFlow, PostgreSQL.

Face Scanning
An interactive solution to obtain a three-dimensional model of patients' faces and the possibility of online editing of these models to provide clients with the opportunity to see preliminary results of surgical operations.

Technologies:
Python, OpenCV, NumPy.

LinkedIn Messaging Flow

Implementing cleaning, text preprocessing methods and multiclass text classifier.

Technologies:
Techniques for class balancing: undersampling and
oversampling, Naive Bayes, SVM, Random Forest Classifier, XGBoost.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent


• Deployed human motion estimation models on triton.
• Deployed text classification model on aws using triton and dynamodb.
• Built the main structure of the das system and its sensor fusion part and implemented it in c++.• I also optimized the AI models in the project by using TensorRt and increased the speed from 19 to 25 fps.
• Developed accurate and smooth road lane detection and tracking using Tensorflow/Kalman filter for the das project.
• Developed pedestrian detection and streaming desktop/non-UI (terminal based) application by fusing camera and radar.
• Implemented deep learning algorithm for Doppler effect based pedestrian detection.
• Built multithreading part and the main structure of multicamera tracking for the cashier less store.
• Adapted cutting-edge action detection technology and trained it on new data.
• Multi camera synchronization
• Multi model deployment on triton server.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: intermediate

• The share of funds obtained from projects under my direct supervision is 40%.
• Implementation of a new employee financial incentive system and increase in service volume by 117.4% (from 2016 to 2022).
• Economic assessment of damages from forest fires in the Luhansk region and development of a commercial model for wood biomass production, considering ecological and energy security requirements, regional social infrastructure needs, and export opportunities.
• 9 business models for utilizing the eco-economic potential of degraded territories to promote women's self-employment and new labor markets, creating value chains in agriculture.
• Deputy Director for Science
• Strategic planning and project management.
• Practical experience in analyzing large volumes of data (SQL, MS Excel) for uncovering hidden patterns and comprehensive hypothesis analysis.
• Development and implementation of machine learning algorithms for predictive modeling and process optimization (Python).
• Creation of visual reports and comprehensive dashboards (MS PowerPoint, Tableau).
• Development of regulatory acts, state standards, recommendations, and analytical reports in response to requests from ministries, departments, enterprises, etc.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: intermediate


Description: 
1) validation and model building based on machine learning. Build an application to automatically validation any model on streamlit and flask. Build a method to test the time series model. Build a scoring model based on mobile data such as Beeline, Tele2. Auto data web scraping and put on AWS servers. Developed an algorithm for optimal filling of 3D space, in particular containers and trucks API for AWS, and visualisation on unity(c#). Build a CV model based on keras, tensorflow for determining the number for barcodes