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


With a Master's degree in AI, a background in computer engineering, and experience as a Software Engineer at Uzinfocom, I am confident in my abilities to contribute to your team and make a positive impact.

During my Master's program in AI, I had the opportunity to work on various small AI/ML projects that allowed me to apply and deepen my understanding of Python programming, machine learning algorithms, and natural language processing (NLP) techniques. One notable project involved developing a Text-to-Speech (TTS) module for the Uzbek language, where I implemented NLP models, data preprocessing techniques, and built a Python-based TTS system.

In my current role as a Software Engineer at Uzinfocom, I have been involved in the development of software solutions for diverse projects. I have actively contributed to the design and implementation of web applications, where I have utilized my Python skills to build efficient and scalable solutions. Working in a collaborative environment, I have collaborated with cross-functional teams to deliver high-quality code and ensure project success.

As part of my responsibilities, I have been actively involved in the development of features and functionalities, performing code reviews, and ensuring adherence to coding standards and best practices. Additionally, I have been engaged in troubleshooting and resolving software issues, ensuring the smooth functioning of the applications.

While I have gained valuable experience as a Python developer and NLP engineer, I am always eager to learn and improve my skills further. I am particularly interested in exploring advanced machine learning techniques, such as deep learning, and expanding my knowledge in areas like computer vision and natural language understanding. I believe that by continuously enhancing my expertise, I can contribute more effectively to projects and help drive innovation within the team.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper

In my most recent role at Bank BPH (part of General Electric), I implemented BI tools and Python into the reporting and model validation processes, greatly simplifying the entire team's work. I also conducted advanced statistical analysis and optimized SQL queries for improved efficiency, resulting in better risk evaluation.
With a strong foundation in model validation, credit risk analysis, and statistical modeling, I have a proven track record of delivering valuable insights and driving business growth using tools such as Python, R, and SQL for almost 3 years. I also have a wide knowledge of different tools regarding Machine Learning, Big Data, Cloud, Business Intelligence, Neural Networks, and others.
I am always seeking out new opportunities to learn and grow. Whether through online courses, attending conferences, or working on personal projects, I am dedicated to staying at the forefront of the field. I am interested in exploring the applications of machine learning, cloud computing, and deep learning in data science and am eager to join a company that values and supports this type of continuous learning.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: fluent


With over 4 years of experience, I've excelled as a Machine Learning Engineer and Data Scientist implementing state of art object detection, and segmentation models using Detectron2 and Yolo, Unet and etc. for geospatial imagery. I've Implemented Optical Character Recognition for documents and deployed data pipelines utilizing Apache Airflow, and Docker. My proficiency also extends to implementing ensemble methods like Lgbm, Xgboost, and Linear regression for different business cases. Additionally, I've managed SQL and NoSQL databases, reflecting my commitment to enhancing data operations.
Position: Data Scientist
Category: Data Science
Experience: 4 years | English: fluent


With over three years of professional experience in the data science field, I began my journey as a mentor for R and Python programming languages. Since then, I have had the opportunity to work across diverse industries including banking/finance, retail, advertising, consulting. 
Throughout my career, I have been involved in a variety of projects such as micro-scoring, IFRS, Churn, Pricing (Interest Rate Rejection) modelling and Time Series Models.
In all of these projects, my main focus was to solve business problems with AI  and drive impact.
Moreover, I have a strong understanding of automating processes and developing pipelines to enhance business efficiency. My skills include statistical analysis, machine and deep learning, data visualization, have a proven ability of extracting insights from large datasets using Python and PLSQL and presenting findings in a clear, and compelling manner to non-technical people. 
Also I have obtained Tensorflow Developer Certificate and possess expertise in Deep Learning methodologies.
Moreover i have my hands on with  broad range of technologies, such as Mlflow, AIrflow, Docker, and Flask (to develop simple APIs ).
Position: Data Scientist
Category: Data Science
Experience: 7 years | English: upper

I mostly proud of my prior data-driven projects which enhanced company growth by 35% over 18 month period
With prior experience as Data Scientist, I’ve created absolutely new data-based systems such as Panel for Managers, KPI system of employees, predictions and simulations for new business cases. Data Mining, EDA, Feature Engineering, Feature Selection, Model Selection, Model Optimization with Hyperparameters, Model scoring and model deployment are some of my duties during my last experience. I also have experience in learning and applying new technologies as appropriate. Additionally, I have a few NLP and Transformer Language projects as freelance.
The size of the company is not an important criterion for me. However, I prefer to work with professionals that I can learn from.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate


With the use of several libraries such as pandas, matplotlib, scikit-learn, I have built Machine Learning model that is able to predict car prices based on data that is collected from the most famous car retailer website in Azerbaijan turbo.az. Other than this, I have done basic sentiment analysis on education field using Vader library.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

I am proud that the results of my work were appreciated by the top-management. That through my work, I can influence the performance of the business.
Work as Machine Learning Engineer in the automation project of the logistics department in Fozzy Group (lead retail chain in Ukraine).
* Creation of algorithms for forecasting inventory using ML methods, probabilistic simulations, classical statistics. In particular, the development of a forecast module for promotions events.
* Also working on forecasting algorithms for new products and cannibalization of products pairs.
* Develop program for day-to-day logistics ordering automatization, which save a lot of time for logistic department workers.
Tools:
- Python 3+ years (pandas, numpy, matplotlib, seaborn, math, scipy)
- ML & AI packages (sklearn, keras, tensorflow)
- RF, XGBOOST, SVM, Logistic Regression, LSTM, ARIMA, Prophet
- R
- SQL

Data Analyst
Work in the project, which goal was to create development strategies of FMCG Commodity Groups, as a result of the research performed. Working with Big Data (internal and external). 
Tasks:
- Analysis of the Commodity Groups product range
- Analysis of promotional campaigns to increase their effectiveness
- Revision of the shelf space for the Commodity Groups assortment
- Analysis of the Marginality's components in order to increase it
- Presentation of the research results to stakeholders in the form of a presentation with visualization
Tools:
Excel, PowerBI, SQL, Python (pandas, numpy, matplotlib, seaborn, math, scipy)
Good salary, professional team, interesting projects.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent

Certified Microsoft Azure Fundamentals 
Certified Microsoft Data Fundamentals 
Certified PCL Data Governance (L1) 
Certified PCL Health Data (L1) 
Certificate from IBM Data Analyst Professional  
Certificate  from IBM and badge for practitioner on Enterprise Design Thinking.
Certificate from IBM and badge for the Team Essentials for Artificial intelligence.
Certificate from NVIDIA for completion of Fundamentals of Deep Learning for Computer Vision 
Certificate from NVIDIA for completion of Fundamentals of Deep Learning for Multiple Data types 
Certificate from NVIDIA for completion of  Deep Learning for Healthcare Image Analyses 
Certificate from Google Cloud for completion of Launching into ML 
Certificate from  Google Cloud for How Google does ML 
Prudential AI Exam Level 2 earned Elite Status for Data Science
Worked across multiple functional departments translating business problems into solvable cases and developed business strategy models for stakeholders.

Identified, measured and recommended improvement for strategies for KPIs to Health and Wellbeing Department.
 
Implemented Automated Pricing Model on MS Azure Databricks and Auto Schedule Reports on PowerBi  for Insurance Company. 
 
Analyzed and processed complex data set using advanced querying, visualizations and analytical tools. 

Worked on Claim & Diseases analyses and presented data insights and conclusions to team in order to improve business strategies and operations. 

Trained binary classification model for Cov19 as classifying COVID or Non COVID.

Trained classification model for predictions of anemia among 5 years old children.

Trained Clustering Model for deep analyses of customer behaviour.

Trained deep learning applications for image segmentation, sentence generation, and image and video captioning.

Trained data analyzing and prepared data visualization on Power BI, Tableau.

Trained how the data should be analyzed and get from database according to system's workflow.

Created dashboard scenarios and write insights of each analyzed data.

Model the data by following machine learning algorithms and record model results.

Created REST APIs in Python using  Flask and implemented ML projects

Determined, using Python clustering methods for group of customers where underwriting models were underperforming.
My primary E-color are Green over Red. Which means my personality style is that of the Doing Thinker. My goals and standards tend to be more rigorous  and rigid those other personality styles. I demand perfection and therefore tend to be critical of myself and others. I'm task oriented and often feel a need to analyze situations until I fully understand. As my expectations I want to start from the original business idea and work through data exploration and data preparation. Then move to model development. Next comes deployment and validating the environment. Finally there's the push to production.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Successfully created and deployed model that helped to detect anomalies, developed solutions for risks that were hard to detect.

Had 2 projects that won first place at university competition 2 times
Worked as Data Scientist, developed DL model for anomaly detection, researched potential risks and developed solution for them

Had non-commercial projects with object detection and facial recognition, where I worked mostly as a software engineer
Position: Data Scientist
Category: Data Science
Experience: 6 years | English: upper

Courses:
"Machine Learning by Stanford University" on Coursera
"Introduction to Probability and Data" on Coursera
"Deep Learning, a 5-course specialization by deeplearning.ai" on Coursera
"Algorithmic Thinking" on Coursera
Worked for two years as CTO in Computer Vision startup.
I was responsible for product architecture/model research and deployment.
Also, I'm good with converting business problem into technical task.

Worked in a several of outsource companies as Machine Learning engineer in computer vision(object detection/segmentation), NLP(chat bots) and Reinforcement Learning(plant control) projects.

Person with strong Computer Scientist background as worked for 3 years as C++ developer.
So I could deploy models to android/ios devices, desktop and Linux servers
Challenging projects.
Flexible workload
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: intermediate


Worked in Course (Python and machine learning instructor), Insurance (Data Analyst Reporter) and Banking Sector (Data Analyst). I am very skilled in visualization tools such as Qlik Sense. Python and its libraries are easy to work for me. I have developed budget model from scratch (budget forecasting) and deployed it as a website. It is currently working well.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate

Education: KNSL 145, physics faculty TSNUK (bachelor degree; 1 year to master degree). Prize-winner of school and students Olympiads in physics and mathematics. Have commercial experience working as service engineer with medical equipment.
Worked in university with science project, using python. Working with FPGA, arduino. Have expirience working with clusters.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: intermediate

Worked mentor on Python free intensive for Beginners.
Knowledge numpy, pandas, matplotlib, sklearn( Train & Test models, Linear and Logistic Regression, SVC, DBSCAN, K-means etc), SQL.
Also have basic knowledge of Django
Worked Mentor on Python Intensive. 
Helped students with the developments of the basics of Python.
Checked their hometasks.
Also made some project in kaggle (Titanic, WestNileVirus).
For predict use Logistic Regression, DBSCAN, SVC, K-means.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: upper

Master of Computer Science, Artificial Intelligence Systems
Worked on computer vision tasks such as object detection, segmentation, classification. 
Worked with recommendation algorithms such as collaborative filtration for the project in fashion industry. 
Also worked as a business analyst.

Skills  
• Python (Scikit-learn, NumPy, Pandas, Matplotlib, Seaborn, nltk, Keras, Tensorflow, Flask) 
• SQL 
• Git 
• Business Analysis
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


Worked on data preparation, data collection (using API and scraping), data management, data analysis (in particular, text analysis), data visualization (Grafana/Kibana).

I am passionate about big data and I want to develop as a data scientist. As an active and results-oriented specialist, I will be happy to strengthen your team.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: intermediate


Worked on developing an application to recognize text information and map it with base rules using NLP/machine learning and parser approaches. I have applied different approaches to analyze and create statistics of input data. Worked on solutions based on NLP technologies such as Parsers, Word2Vec, Doc2Vec, RNN. I also worked with Docker, Jenkins, Databricks. Worked with many, not main tasks such as face recognition, object segmentation,  image classification  and other tasks related to computer vision
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: intermediate


•	Worked on the development of a tool for advertising fraud analytics.
•	Developed a ruleset, which made possible to detect advertising fraud more interpreted than ML models.
•	Made cluster research analysis of ad impression data.
•	Developed features for real-time fraud detection.
•	Wrote several wrappers to represent a mobile game in the form of a mathematical model.
•	Trained bots to play games using Reinforcement Learning.
•	Built a model that analyzes the churn-rate of users from a mobile game.
•	Built several models to detect anomalies in network traffic.
•	Worked on building an infrastructure for detecting malware in a Linux system.
I'm not interested in doing computer vision
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Run startup project for free parking places detection, participated in several hackathons, won 2 grant competitions. Received a second degree diploma in the ICPC semifinals.
Worked with data from physics and medicine. Trained ML models (neural networks, boostings). Currently implement pipelines for big data processing (crowdsourcing).
Product project with motivated team and research tasks. Do NOT want to work only on data parsing and writing simple SQL queries.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: intermediate


· Worked with McKinsey to build Stress Testing models for banks and insurance companies to mitigate the risks in decision making. 
· Used statistical approaches and Python language to build an automated tool for time-series modelling. Utilised from the Dash to transform the tool into a visual and interactive interface for non-technical people.
· Constructed customer behavior and segmentation models using ML techniques in Dataiku. 
· Implemented search and matching algorithm inside of e-commerce system for Azerbaijani language in Python. 
· Built a predictive employee churn model to identify possible attrition risks in Dataiku + Python.
· In the scope of Data Governance developed visual tools to analyse and report data quality using Python + Power BI. 
· Built data sharing process for cross-company data exchange. Integrated Dataiku platform for data exchange and in-place analysis and modelling purposes. Built data masking and unmasking pipelines for data sharing procedure.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: fluent


Worked with speech processing and Deep Learning on a speech emotion recognition project;
Worked with autoregressive language model (Transformer) for question answering on a set of technical reports about the use of pesticides in crops in Brazil;
Worked with time-series prediction ML pipeline for prices of beef (exportation), using many variables, including demand and prices of commodities.
Worked with operational optimization and derived a mathematical model for the cost function in order to reduce the time of the allocation optimization process.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

•	Developed and implemented a working project for cyberpolice department as backelour graduation work;
•	Developed AI/ML decisions for medicine;
•	Working on many commercial projects as time-series analysis, best advertisment campaign prediction, etc.;
•	Had implemented distributed learning on two servers with GPU using the horovod framework
Worked with:
•	Time series processing: analysis and pattern extraction from time series. Clustering time series based on extracted patterns;
•	Image processing: image denoising and deblurring, image segmentation, image feature engineering using the Fourier analysis and Gauss transformations, image preprocessing. Clustering of segmented images by their feature vectors;
•	Retail: customer segmentation, selection the best marketing companies based on their impact on customer.
•	NLP: medical articles processing, extracting sentence embeddings, training multiclass-classifier of embeddings.
Technology stack: 
•	Programming languages: Python;
•	Frameworks, libraries: pandas, numpy, matplotlib, seaborn, yellowbrick, PIL, Tensorflow 2.0, Keras (CNN, GAN, AutoEncoders, DataGenerator, Optimizers), PyTorch, huggingface models, scipy (fft, affine_transform, gaussian_filter), XGBoost, LightGBM, scikit-learn (SVM, RandomForest, K-Means, DBSCAN, KFold, GridSearchCV), horovod (used for distributed learning);
•	Tracking and VCS: neptune.ai, git;
•	IDE’s: Jupyter notebook, Visual Studio Code, JetBrains PyCharm.
•	Databases: MSSQL
I’m familiar with math, probability theory and statistic. Also have experience with Java and C++.
The main criterion for me is the interest of the project. So I expect that the new cases at work will be non-standard, complex and extremely interesting.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: intermediate

CERTIFICATES:

* Python - The Practical Guide
* Docker and Kubernetes: The Practical Guide
* How Google does Machine Learning
* SQL for Data Science
* Structuring Machine Learning Projects
* Sequences, Time Series, and Prediction
* Neural Networks and Deep Learning
Work experience:

1. Machine Learning Engineer (04/2023 – 06/2023):
- Built an accurate image classification model using PyTorch, FiftyOne, FastDub, ClearML, BentoML, FastAPI, and Gradio.
- Developed an OCR model for a specific task using PaddleOCR and YOLOv5.

2. AI Engineer (10/2021 – 03/2023):
- Created an object detection model for waste classification using PyTorch, TFlite, OpenCV, and YOLO.
- Researched neural network-based solutions for generating 3D objects and animations from images using NeRF.
- Built models for price prediction and image denoising using various libraries and frameworks.
- Developed a custom image classification model using TensorFlow, Keras, OpenCV, and Docker.

3. Junior Data Scientist (01/2021 – 10/2021):
- Developed object detection algorithms using computer vision and deep learning techniques.
- Implemented object detection and hand tracking using OpenCV and YOLOv5.
- Worked on NLP tasks such as text recognition and classification.

4. Junior System Administrator (09/2020 – 11/2020):
- Provided technical support, installed software/hardware, diagnosed and solved network problems.

Personal projects:
- Deep learning: Developed neural network models for bird sound classification (graduation work).
- Numerical methods: Implemented the Implicit Milne's Predictor Corrector method for the Lotka-Volterra model (course project).
- Optimization methods: Explored the Conditional gradient method with automatic step selection (course project).
- Deep learning: Developed recurrent neural network models for air pollution forecasting (graduation work).
- DataKyt: In-progress project for recording equipment using Python and SQL.
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: fluent

Not too much to say, but I am a Ukrainian Women Chess Champion  U20
Work experience: 
Jr Data Scientist, Co-Founder
Hard skills:
Data preprocessing, data visualization, developing quantitative algorithmic systems for trading, applying Machine Learning to asses the algorithm's risks in financial markets. 
Soft skills as a Co-Founder: 
Project management, market research, working directly with clients to adjust their portfolio management to their preferences
Education: 
BS Mathematics CS minor (Texas Tech University)
BS Mathematics (University of Missouri)