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


Experienced Data Scientist/Machine Learning Engineer with a demonstrated history of working in different areas, including software development and e-commerce. My skills include, but are not limited to Python, Statistics, Mathematics, SQL, Cloud Computing services, etc. Strong data science professional with a Master's degree focused in Applied Statistics.
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 5 years | English: upper

- Building ML models and BI applications from scratch
• Hands-on experience in machine learning, business and data analytics, BI, statistical and econometric modeling
• Focus on financial, telecom and energy sectors
• Python, R, C#, SQL, Tableau
Machine Learning with applications in financial services, energy or telecom industries
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

Accomplishments:

** AWS Machine Learning Certification 
** Earned Master’s degree in ITM (Innovation Technology Management) from University of Tartu
** Certified TensorFlow Developer
** Ex Visiting Researcher CSB Group at University of Cambridge
** Winner of "The Open Data Hackathon for Municipalities"
** Top achiever in Kaggle Data Competition Awarding institution: E-GOV Development Center
I am an AWS Machine Learning Certification holder and Certified TensorFlow Developer, which provide me with qualifications to implement deep learning solutions for given business problems.

My work experience has given me the opportunity to work on projects involving machine learning and deep learning algorithms. Over the projects I have worked on, I have gained tremendous experience in writing production-grade software and implementing ML pipelines in production. 

Highlighted projects:

* mT5 based Azerbaijani News Summarization;
* New product demand forecasting via Content based learning for multi-branch stores;
* Building face liveness detection engine for spoofing face recognition;
* Automating Customer Support with NER (Named Entity Recognition) in the Azerbaijani language;
* Developing session-based recommendation system for e-commerce website;
* Satellite Images to real maps with Pix2Pix generative adversarial network;
* Norvig's Spell Checker Algorithm for Azerbaijani Language;
* Detecting Weapon Objects by using one-stage object detection model;
* Predicting Credit Card Fraud by using AWS Random Cut Forest;
* Tacotron-2 text-to-speech Tensorflow implementation;
* Generate Synthetic Images with DCGANs in Keras;
* Scraping Azerbaijani real estate website and sending whatsapp message with AWS Lambda
* Clustering: Opening a New Restaurant in Baku;
* Applying perspective transformation and homography to build OCR engine and etc.
To utilize a larger array of ML/Data science tools and face a variety of issues to grow professionally and become a senior level ML engineer.
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 4 years | English: fluent


I have 4 years experience in Machine Learning and Data Science. 
Mostly was focused on computer vision projects, worked with different tasks among them object detection, semantic segmentation, OCR, pose estimation, image classification.
Have deployed models as web services and on edge devices.
Have experience with Data Science projects from start to end: data collection/extraction, data processing, feature engineering, model development, parameters tuning, validation and testing,  deployment.
Have some experience with NLP.
Apart from engineering tasks, my responsibilities were: to understand the requirements and the scope of work, estimate timelines, design the solution architecture, validate it with clients, lead the project implementation, mentoring.

M.S. degree in Computer Science.
remote
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

I've owned and led projects end-to-end in every job I've had. I have experience in researching, developing and deploying both deep learning and classical ML models in an efficient and scalable way. I've mostly worked on NLP and time series-related tasks in industry. Currently applying reinforcement learning methods to language modelling (both with and without human feedback).
I have considerable experience in deep learning for NLP, time series forecasting, and MLOps, among other things. My experience includes owning projects from start (research) to finish (deployment and improvement).
Notable projects include a retrieval-oriented language model fine-tuned with reinforcement learning, a zero-shot Document AI suite for resumes, machine transliteration for low-resource languages (Urdu, dialects of Arabic, etc), and a scalable autoML forecasting system that beats Vertex AI and is comparable to AWS Forecasting while being much faster.
My educational background is in Computer Science and Economics. I hold a Master's degree in Economics and Data Science from Bocconi University and am currently pursuing a second master's in Machine Learning from Porto University.
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper


I've been working on such machine learning projects using PyTorch:
- digit recognition on MNIST dataset (DNN and CNN implementations)
- multilabel comment toxicity classification (via bag-of-words and via 1D CNN with word embedding)
- image denoising (using encoder-decoder approach)
- camera model classification with given photo (via fine-tuning mobilenet v3)
- iris classification

I consider the most exclusive and valuable skill that I received from aforementioned projects is deep understanding of math behind used ML and image-processing algorithms. So I have strong basis and I want to develop in more advanced techniques.

Also I've been working on data scraping and cleaning task of collecting movie info from IMDb using BeautifulSoup and selenium.
I would like to work in computer vision, NLP, recommender systems or other machine learning branches. I'll gladly take responsibilities of collecting and processing data, composing models architecture and training them, making something new based on insights.

I'm not interested in EDW projects.
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 3 years | English: upper


Knowledge of classic ML algorithms (Linear regression, Logistic regression, Random Forest, etc)
Experience with Python, Jupyter, NumPy, Pandas, Scikit-Learn, H2O.
Time Series, tabular data analysis.

Strong mathematical background.
3+ years experience in data analysis.
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate


Lead System Engineer
Assistance in organizing work of System Engineers Team, as well as performing system administration
tasks.
Achievements include:
Automated tasks using Powershell:
• Get computer program list by regular expression
• Install/Uninstall application on computer remotely using msi/exe file
• Install Windows update on computer remotely using cab/msu/exe file

Magento Developer
Project support and development of extensions for Magento 1 and Magento 2.
Achievements include:
• Adjusted 60,000+ music albums links to Amazon and LastFm
• Automated import of 600+ products containing 80+ attributes, including images
• Automated import of 5+ attributes for each of 900+ products
• Developed "Social network links" extension, including REST API
• Developed "Banner list" extension, including REST API
• Developed extension for managing lists of customers' favorite products
• Developed extension for managing warranty page

PHP Developer
Development of applications based on Yii2 framework. Refactoring of existing projects.
Position: Machine Learning Engineer / Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Completed **Data Science Certification at DataCamp**.
 
It consists of 3 steps: 

 1. Pass 4 tests:
    - Python Coding
    - Statistics
    - PostgreSQL
    - Model Development

 2. Coding Challenge
 The task was to transform raw data into a specific form in order to fit the shown example.

 3. Case study
  I was given a project and had 24 hours to finish it and then present findings to a person who has no technical data science background. Then my project has been reviewed and graded by data science experts.
Trainee Data Scientist (7 months) 
- Write SQL queries in order to get required data.
- Explore DataScience pipeline (from Business Understanding to Deployment). 
- Project 'Analysis of open data': Web-Scraping, Data analysis, Data cleaning/transformation,Feature Engineering.
- Lead ML Engineer role for NLP Model Development (Task Definition and Description + Development).

Projects:

| NLP with Disaster Tweets
Made feature engineering and interesting plots. 
Used Spell Correction and Stemming techniques on text.
Wrote own classes which split data into numerical and category; transform text using built-in pipeline with CountVectorizer, TfidfTransformer and PCA; transform ordinal features using OneHotEncoder.
Finally wrote LSTM nn using PyTorch and put everything in Pipeline. 

| Digit Recognizer
The aim was to correctly identify digits from handwritten images.
Made CNN model with final accuracy 98.5% using Keras.

|  Bank Clients
- The main idea is to predict if client subscribed a term deposit (Binary).
- I wrote own classes in order to process data. Finally made pipeline with Random Forest and used GridSearchCV to find the best parameters. 
- As a result, got a model which can receive raw data, prepare it by itself and return predictions.

|  Used Cars Sales
 Predict car price which should be in range +- 1500£ from competitors price. Made own metrics to evaluate model output which finds the percent of cars which would be sold and percent of cars which would be sold for a good price - not too low (means lose money) and not too high (if price is too high customers will prefer our competitors).

| HousePrice 
Created visualisations using Plotly.
Then prepared dataset and wrote function which finds MSE, RMSE and R^2 for train and test and returns scores dataset with a new model performance observation. 
Finally used Keras to create a Sequential Neural Network.

| FakeNewsDetection
University project, which will help people to avoid fake news.
Created NLP model in order to classify news.

|  Other projects
- Motorbike Ambulance Calls: How many ambulance calls will be per day depending on weather conditions, precipitation, time and season.
- Mall Customers: Cluster customers by their age , income and spendings.
- Ukrainian Coffee Shop Market: Analyse and cluster existing coffee shop market.
- Iris Clustering: Clustered data using KMeans and created own metrics to evaluate model (also prepared a picture of how it works).
Position: Machine Learning Engineer · Data Scientist
Category: Data Science
Experience: 1.5 years | English: intermediate

I am a reliable person, persistent in my work. In difficult situations, I always found a way out.
I have been working with data, source, and transform the data into the structures needed for various enterprise requirements. I have developing accounting, financial, processing modules, maintaining distributed databases providing consistency and completeness. I would like to shift my career path. In Desember, 2019, I finished one-year master course Master’s of Business and Management in Artificial Intelligence and Data Analytics at Kyiv School of Economics, Ukraine (KSE). I'm learning through courses, books, conferences, practical tasks. I am a person with high potential, willing to learn new things and a positive thinking. The main thing I like the most is problem solving. The first idea of something complicated is one that has been explored for years, or perhaps nothing seems simpler than it's solution. That feeling when you come up with this "impossible" result, is more than worth the effort. As a Chief software specialist my goal is to help solve customers' problems so they can do their jobs better; and that way bring revenue.
to build models that will be worth for companies,
to raise my competencies.
Position: Machine Learning Engineer, Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

Work:

Machine Learning Engineer:
Topic modeling of 3 Million technician remarks. Development of the application that enables technicians to compare their actions with other technicians who had to deal with similar elevator breakages. 
Monitoring of Elevator status using Computer Vision.

Data Scientist:
In a small team developed a content-categorization pipeline of social-media posts, which resulted into near human-like performance and is constantly used in the production.

Our team also managed to develop a Django-based social-media monitoring application, which resulted into drastic increase the company's data-workflow efficiency. 

Business Intelligence Consultant:
Together with a small team developed a working planning-model for an Online Retailer in 3 days.

Directly supported the Senior Project Manager in the development of a new resource planning model for a big energy company after immediate superior left the firm.


Academia:
Won several town and region competitions in mathematics and physics. Third place in the final stage of the "small academy of sciences in Ukraine" competition with a scientific study in the experimental physics field.

Europa-Universität Viadrina "Fast-Track" scholarship for international students from Post-Soviet countries.  

BURG Scholarship for outstanding academic achievements and social engagement.
04.2021 - present : Machine Learning Engineer at Schindler AG in Berlin. 
As a member of Data Science team, I am responsible for development of reproducible pipelines covering each stage of Machine Learning operations including model training, validation, deployment and monitoring. Focused on predictive Maintenance domain. 


07.2020-04.2021: Data Scientist in the German's leading Social Media Analytics company in Berlin. We managed and analyzed social media data of dax-30 companies.

02.2019-06.2020: Business Intelligence consultant in Berlin. Main fields of focus: online retail and manufacturing. Implementation of Enterprise Resource Planning systems for large German and UK companies.



My technical and academic background combined with my previous working experience have prepared me well for a role that is analytically complex. 
Interested in machine- and deep learning. Constantly exploring these fields and trying to integrate new state-of-the-art algorithms in business domain.
- experienced team, which is eager to exchange knowledge.
- machine learning projects in business domain.
Position: Machine Learning Engineer, Data Scientist
Category: Data Science
Experience: 0 years | English: upper

Certified Associate Data Scientist at Datacamp.
I don't have any experience in the company or freelance. I am the young man, who wants to become a greatest Data Scientist one day. 
For now, i have done a few mini projects where i used CV, NLP, and traditional machine learning.
The only field where i want to work is Data Science, and i prefer more Machine Learning Engineer roles.
Position: Machine Learning Engineer, Data Scientist
Category: Data Science
Experience: 5 years | English: upper

Developed different interesting educational materials to help people to study Data Science.
Helped client (cloud-based inventory management retail company) to implement functionality to predict sales volume for promotion periods, which led to a more accurate calculation of the volume of orders for new batches of products.
Assisted with developing a Deep Learning platform for studying physical activities which compares teacher’s with student’s movements in a live video.
I have diverse experience in different Data Science fields including classic Machine & Deep Learning projects, developing API's, working with Docker, etc. Also, I have experience in project management and team leading.
Seeking for interesting tasks and a good team.
Not interested at Computer Vision
Position: Machine Learning Engineer, Data Scientist
Category: Data Science
Experience: 3 years | English: fluent


Research Fellow, Boston University
• Applied Machine Learning techniques towards intricate problems in biophysics and complex systems
• Theoretically and computationally investigated Phase Transitions in Complex Systems, studied Liquid-liquid phase
transitions, as well as out of out-of-equilibrium dynamics with and without external source
• Performed multiple parallel simulations in C on the scientific cluster using Bash, analyzing vast amount of data via Python
and applying numerous statistical techniques to verify the  theory of the models.

Deep Learning Specialization by Andrew Ng, DeepLearning.Ai:
Neural Networks and Deep Learning; Improving Deep Neural Networks: Hyperparameter, Tuning, Regularization and Optimization; Structuring Machine: Learning Projects; Convolutional Neural Networks; Sequence Models.

MAIN PROJECTS
• Identification of Phase transitions of Ising Model
- Classified phases of 2D Ising Model via Logistic regression, Random forests, NN in TensorFlow
- Classified phases of 2D Ising Model via CNN using PyTorch and TensorFlow
- Learned effective low-dimensional representations of equilibrium samples via Variational Autoencoders with Keras
- Employed Generative Models (Generative Boltzmann Machine) to learn a variational approximation to the probability distribution used to draw thermal spin configurations in the 2D Ising model
• Prediction of Stock Market Prices of S&P 500 with machine learning
- Collected data from WRDS including monthly fundamental and return data since 1980-1-31 to 2017-12-29 for 17324 companies using SAS code and cleaned the data using Python
- Predicted monthly returns using machine learning techniques, such as LASSO, Random Forests and k-nearest neighbors
- Fine-tuned the models to increase the accuracy of the prediction models to maximize the returns of chosen portfolios
Position: Machine Learning Engineer/ Data Scientist
Category: Data Science
Experience: 2 years | English: fluent

Own generator and starlink
Worked with NLP methods of sentiment evaluation of companies mentions in different sources (news/social media).
Worked with churn prediction and analysis for major telecommunication company.
Implemented models of age/gender prediction and deployed to Google Coral Dev Board.
Have managed to built ETL-pipeline using Airflow and AWS services.

Tensorflow/keras for building DenseNet (classification by image) and ResNet transfer learning (classification by sound). gRPC for inference in microservice.

Developed DNN model using keras based on ResNet architecture for multi-label classification.

Kaggle top 8% percent (bronze medal) in competition
I haven't figured out yet which sphere tempts me the most: CV, NLP, or working with tabular data. But, it would be fascinating to apply the ML/DL in the medicine domain, though I'm still want to use my knowledge in different domains.
Position: Machine Learning Engineer/Data Scientist
Category: Data Science
Experience: 3 years | English: upper

Master's degree in statistics.
Around 3.5 years of commercial experience in machine learning and data science. 

Last project on which I worked was developing  pricing algorithm for revenue optimization.

Time Series Forecasting, Predictive modeling, Anomaly Detection, Cluster Analysis, A/B test analysis
NLP (text classification, text summarization, information retrieval)
CV(image classification, object detection, object tracking)
I'm not looking for data engineering positions or MLOps/DevOps positions
Position: Machine Learning Engineer/Data Scientist
Category: Data Science
Experience: 1 years | English: upper

2nd place in University project with Softserve
- Neural Networks and Deep Learning
Coursera, Online
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Coursera, Online
- C++ and Web
Lviv Polytechnic National University, Lviv, Ukraine
- The Structured Query Language (SQL)
Coursera, Online
- Relational Database Design
Coursera, Online
- Advanced Topics and Future Trends in Database Technologies
Coursera, Online
Education:
2021-2025 - Bachelor's degree (in progress) in Applied Mathematics and Informatics.

Professional experience:
I have been working as a Data Scientist in a University startup with Softserve company. My primary responsibilities included the development & testing of new features on a project, like: fake news detector, checking reported news in DB, enc.
Apart from my experience in Machine Learning, I'm interested in NLP and Recommender Systems applications.
- Long-term position
- Challenging problems to work on
- Informal and friendly atmosphere
- Working in a team of professionals
- Some Image processing tasks
Position: Machine Learning Engineer/Data Scientist
Category: Python
Experience: 5 years | English: upper


Machine Learning Engineer - ENGINEET
May 2021 - Present

•Design Machine Learning system.
•Assist in model development, research and implement appropriate ML algorithms and tools
•Developed an algorithm to understand customer behavior
•Complied data from various source to perform complex analysis for actionable results
•Utilize machine learning algorithms such as linear regression, multivariate regression, naïve bayes, Random Forest, K-Means and etc. for data analysis
•Developed Clustering algorithms and Support Vector Machines that improved customer segmentation and Market expansion
•Worked on NOSQL database like Cassandra
•Main source of Business Regression report
•Design and build a text classification application using different text classification models
•Created charts in Jupyter Notebook to perform analysis & visualize data using Matplotlib 
•Define data augmentation pipeline
•Find and implement the right algorithms and tools for NLP tasks
•Developed NLP systems according to requirements
•Extend ML libraries and frameworks to apply in NLP tasks

Data Scientist - Wood World LLC
January 2017 - May 2019

•Worked independently or collaboratively to select a specific set of vendors that can support multiple guests
•Analyzing internal operations, evaluating how effectives and efficient they are compared to similar other businesses in the same field
•Forecasted on multiple products about their demand, pricing and predicting inventory management 
•Used PySpark to speed up the execution process 
•Predicted feature outcomes with current data management order
•Developed python programs for manipulating the data reading from various Teradata and convert them into one csv file
•Performing statistical data analysis and data visualization using Python
•Create reports based on findings to be presented to executives at monthly board meeting, making recommendations for improvement in addition to raw information.
Position: Machine Learning Engineer/Data Scientist
Category: Data Science
Experience: 5 years | English: upper

Experienced in FMCG, NLP, computer vision(especially). Working a lot with neural networks(architecture building, optimizing inference time/memory usage) and classic ML algorithms.
Machine Learning(supervised, unsupervised), Deep Learning(PyTorch, Tensorflow), Probabilistic programming(PyMC, Pyro, Edward), Python(numpy, scipy, scikit-learn, pandas, etc), Data Visualisation(matplotlib, seaborn, bokeh), SQL, NoSQL(MongoDB, Cassandra), GBM frameworks(Xgboost, LightGBM, CatBoost, etc)

Web - Flask, aiohttp, docker
Team leading experience
Data Science/ML/Deep learning projects(probabilistic programming/bayesian approach usage is a huge plus)