lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Senior Data Scientist
Category: Data Science
Experience: 3 years | English: upper

Participated in number of projects in different fields like Finance, Project management, Chat Bots, Anomaly detection, etc. Implementing solutions in following directions: 
•	Machine learning algorithms
•	Deep Learning
•	NLP
•	CV
Some latest projects
- Cognitive assistant for project resource planning
(Predict staffing mix for project, total and on weekly basis)
- Finance smart assistant / recommenderplication 
(Сompanies merge and acquisition recommender tool)
- Telegram bot for monitoring goods delivery service
(Unofficial bot for monitoring and notification open delivery slots for big online service of goods delivery from 5 main store chains working in more than 14 cities) 
- Social chat monitoring tool
(Twitter sentiment analysis for desired company/tag)

Tasks:
Exploratory data analysis, data cleaning, imputing, etc.
Data preprocessing, feature engineering.
Developing supervised and unsupervised ML models.
Implementation and comparison of different clustering algorithms.
Anomaly detection analysis and automatic outlier elimination methods.
Implementation of different algorithms for enriching input data by synthetic data generation.
Model deployment and model retraining using Azure pipelines.
+ New technologies, frameworks;
+ Free to poropose and try new ideas, solutions;
+ Interesting challenging tasks;
+ Work on real valuable product; 
+ Business trips / relocation;
Position: Senior Data Scientist / Computer vision / Machine learning engineer
Category: Data Science
Experience: 6 years | English: fluent

— Developed a high-performance cross-platform, cross-language (WebAssembly included) computer vision library;
— Developed a high-accuracy, high-precision eyetracking model;
— Ongoing PhD in infectious disease modeling.
2016-2018
Machine learning engineer. Responsible for development of portable eyetracking solution.
2018-2022
Machine learning engineer/Head of Data Science. Responsible for the development of high-load distributed user's involvedness measuring solution by exploiting eyetracking, emotion and attention measurement technologies.
2019-2022 (part-time)
Lecturer. Responsible for teaching a Machine learning/Deep learning course.

Skills/technologies:
— Software engineering (programming, parallel computing, system architecture);
— Machine/deep learning (data analysis, regression/classification, clustering, anomaly detection, deep neural networks, CNNs, RNNs, semantic segmentation, image enhancement);
— Deep learning model deployment (frontend, backend);
— Computer vision (image processing, 3D pose estimation, 3D object reconstruction);
— Mathematics (statistics, calculus, linear algebra, optimization theory);
— Formal language theory, programming language design;
— System modeling;
— Database design/management;
— Mentoring;
Position: Senior Data Scientist/ Data Engineer
Category: Data Science
Experience: 6 years | English: upper


- Over 6 years of hands-on experience of applying Machine Learning techniques in E-commerce, Investments, Retail, AdTech,  FinTech etc.
- Designing, developing, integrating and maintaining complex AI-powered solutions
- Extensive experience of delivering high-performing and scalable Machine Learning applications into production
- Able to translate business requirements into clear technical specifications (ML roadmap)
- Strong problem solving skills and business value oriented
- Capable to interpret model performance and suggest ways to improve it, not just report metric
- Making use of A/B testing to support data-driven decisions
Position: Senior Data Scientist / Data Science Manager
Category: Data Science
Experience: 3 years | English: upper

My latest predictive models saved a ton of human workforce, reduced the cost of services and helped top-executives to plan the future in times of uncertainties

Created algorithms for more accurate targeting, which improved CPM, CPV metrics up to 70% comparing to traditional methods

Also, I have experience in leading the development of new products / solutions. I have 3 people under my command at the moment.
My latest projects:

- Worked on models for predicting the number of parcels / money transfers / etc. for each branch in a region as well as the total traffic for the region (which helped to reduce the number of employees needed thanks to the more accurate scheduling)

- Developed and implemented models for EBITDA predictions (which saved up to a week of work per month for 10 people from accountant department and helped sales team to plan their load on-the-go)

- Developed and implemented the architecture for monitoring system for different departments (which continuously supports and updates 12,000 dashboards), as well as automated reports for top-executives of the company

Also, my other work:

- Clustered web traffic and internet resources (using NLP, vector representations, graph analysis, etc.)

- Created and implemented sentiment analysis model for user comments/posts/replies on the web (intense data cleaning)

- Created pipelines for automated data processing and prediction, telegram bots for alerts systems, parsers using playwright / selenium / beautifulsoup etc.
Position: Senior Data scientist / Data Science Team Lead
Category: Data Science
Experience: 5 years | English: upper


I have over 5 years of hands-on experience in solving real business problems using a data-driven approach, particularly machine learning models. For the last 3 years, I have focused on creating reliable machine learning systems in cross-team cooperation. Experienced working in a high-load environment with an appropriate amount of data. Built models for tabular data and human texts (NLP).
I prefer long-term and complex projects and want to develop in people management. Interested in a leadership position.
Important:
- challenging business-oriented tasks;
- ability to have an impact on the product;
- progressive, result-oriented environment.
Position: Senior Data Scientist / Engineer
Category: Data Science
Experience: 5 years | English: fluent

Helping a huge company in becoming a data driven organization.
Building a successful recommender system from scratch.
Winning 3 hackathons (out of 3).
Data pipelines using Big Data tools (Hadoop, Hive, Spark, HDFS) and Python's data stack
Data Science
Python backends
Ad-hoc analytics
A/B Testing
Text Mining
Machine Learning
Recommender Systems
Code reviews
Familiar with Scala (novice skills)
Position: Senior Data Scientist, Lead Data Scientist
Category: Data Science
Experience: 8 years | English: fluent


I have 7 years of experience in executing and leading data science projects in a wide range of industries. In addition to solid understanding and practical experience with machine learning, my biggest assets are my ability to quickly grasp the complexity of the business domain and to come up with non-trivial data science solutions and insights that solve sophisticated business problems.

I get motivated by challenging projects that require me to learn something new and allow me to be an effective team member and, if necessary, a leader. I believe that communication is an important key to success of any project, and I thrive in situations where I have to frequently communicate with different project's stakeholders to make sure that the project doesn't lose its momentum.
Position: Senior Data Scientist / Machine Learning
Category: Data Science
Experience: 10 years | English: fluent

I developed Data Science part of recommendation system engine which allowed to attract new clients and increase the commission of our company by 10%. The revenue and KPIs of clients that used our recommendation engine increased by 20% average.
I'm a data scientist and research professional experienced with data mining, machine learning and Big Data. PhD holder in economics and math modeling.

Knowledge and experience:
1) Data Science:
- Data processing and manipulation: SQL, noSQL (MongoDB, Redis, Hive - Hadoop), Amazon (Athena, S3);
- Visualization and Reporting: MicroStrategy, Google PLX Dashboards;
- Statistical modeling and machine learning: SAS, R, Python;
- Wide range of modeling techniques: classification, segmentation, regression, recommender systems, web scrapping, NLP;
- Server Deployment (Bottle framework) for online training and prediction processes;
- Neural Networks - Keras.
I am flexible and have experience of working in a corporate companies and startups. I prefer respectful relation between employer, employee and colleagues and healthy environment in the team. I am collaborative and always ready to provide help or a piece of advice to my fellows.
Position: Senior Data scientist & Machine learning engineer
Category: Data Science
Experience: 11 years | English: upper

Factorisation machine model for dense 3 dimension data with AdaMax optimization.
Classification with BigArtm topic model.
Boosting for  classification model with constraints.
Classification video.
Boosting for  list ranking models.
Sequential Pattern Mining Classification.
Recommend System 
Real time bidding model 
Fraud detection model
over 17 projects in Machine learning, 10 years experience, supervise and unsupervise.
RecSystem , Video & Image Clasification, Prediction, Deep learning,  NLP, Time series, Real time bidding, Fraud detection
10 years Python experience
5 years R experience
Interesting tasks, new experience
Position: Senior Data Scientist / Machine Learning Engineer
Category: Data Science
Experience: 6 years | English: fluent


I'm a data scientist with more than three years of professional experience. 

I started as a machine learning researcher at a deep tech startup, mainly doing research and contributing to the core tech. Our primary focus was sequence-to-sequence modeling for speech generation.

Since then, I've transitioned to a traditional data science role working for an online classified/marketplace with a "release early, release fast" approach to development, high product experimentation culture, and great emphasis on user feedback. There I was involved in building an ecosystem of computer vision microservices (e.g., classification, similarity search, quality assessment) for automatic advertisement posting & development of a recommender engine. For the last year, I was a product owner of the whole data science ecosystem, managing a small team & constantly reporting to the C-level. 

Those positions allowed me to gain necessary skills to build a complete data science solution carrying it through all stages, from research and development to deployment and quality assessment. 

The primary area of my expertise lies in recommender systems, computer vision, generative modeling & classic data science (clustering, classification, etc.)

Currently, I'm looking for a new project to apply all my skills and make an impact.
An ideal option is a mix of research/modeling and development/deployment. I have some experience in a productionization & deployment of my models, and I view it as a common part of data science solution development. However, I'm not seeking any pure data engineering position.

I'm open to both full-time and part-time options. Remote positions are more preferable.
Position: Senior Data Scientist / Machine Learning Engineer
Category: Data Science
Experience: 6 years | English: fluent

Kaggle Competition Expert level.
Solving non-trivial tasks with big chunks of data(~80 TiB).
More than 500 successful hours on upwork(top rated profile, which has been deleted by myself due to disagreement with the recent Upwork policy).
My own stock API in Python(fetching, processing huge stock data by means of correlation analysis).
Handwritten OCR project that uses NIST database and Caffe's CNN.
Gesture recognition system for android game(decision tree).
Video streaming and recognition results of video game.
Created a simple android app and published it on play market(>10K downloads).
Technologies: Python(4 years of commercial experience), C++(2 years of commercial experience), R(1 year), Golang(0.5 year), complex math algorithms(function optimization, regression analysis, classification), multithreading, concurrency, asynchronicity, image processing, recognition, graph algorithms, optical character recognition, deep learning, active shape models, statistics, gradient boosting methods, natural language processing.

DB experience: SQL, MongoDB, Elastic, Redis, BigQuery, Postgres
Environments, tools: MSVS, Qt, Pycharm, Clion, Eclipse, OpenCV, Matlab, Octave, R Studio, numpy, scipy, pandas, git, subversion, keras, tensorflow, torch, jupyterhub, aws, docker, jupyter

OS: Windows, Linux(preferable)

Successful completion of Deep Learning Specialization series of
courses with a certificate.

Finished MOOC coursers(no certificate):
-- Data Science(mining, machine learning, statistics etc)
-- Machine Learning 
-- Big Data(Hadoop, PySpark etc.)
-- CUDA
I am interested in applying cutting-edge technologies like deep learning.
I am very fond of jobs where my skills are used properly and I can show myself.
I may review my compensation expectation(down to 2.5K$) and willing to relocate if the work is about getting a Ph.D. degree in my field.
Position: Senior Data Scientist | Machine Learning Engineer
Category: Data Science
Experience: 6 years | English: fluent

1. Successful customer engagement: developed a PoC that made a huge enterprise purchase our product.
2. Author of several Machine Learning research papers (international conferences).
3. Consulted for several ML research projects.
I have rich experience in commercial and R&D Data Science projects.
* Succesfully delivered to production different DS solutions: NLP, Deep Learning, Recommender Systems, and Computer Vision.
* Participated in presale activities, projects estimation, mentoring and supervising junior team members

*  Successfully finished projects include: 
-    real-time video stream processing for object detection, tracking and analytics gathering.  
-     recommendations, demand forecasting and data analytics for retail
-     customer support automation with chatbots and email processing, scalable text sentiment analysis.
Position: Senior Data Scientist | Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: fluent


Technical Skills:
- Data analysis: SPSS, Tableau, PowerBi, Statistics, R
- Programming Languages: Python, R, (SQL-oracle database)
- Machine Learning: Regression, Classification, Clustering, Time-series, dimensionality reduction, hyperparameter tuning, pipeline creation, Boosting, Bagging. Docker, Pickle, Streamlit.
- Deep learning: Pythorch, FastAI, OpenCV, Tabular, Computer Vision, multi-label multi-class classification, NLP, sentiment analysis, Tensorboard, GAN, transfer learning. Mediapipe, Flask, FastAPI

Soft Skills:
- Team leading
- Management
- Critical thinking
- Adaptability
- Solution Orientation
- Communication
- Conflict management
- Stress tolerant 

- Previous work experience:
Data Scientist team leader
QSS Analytics
2020 - Present,
Responsibilities: Including collecting past and present data,
analyzing collected data, using relevant computer software,
finding ways to improve operations and reduce costs, managing a
team of data scientists, planning data projects and providing the tools needed to make strategic decisions.

Mathematical Modelling Junior Scientist
Azerbaijan National Academy of Science
2021 - Present,
I work cross-functionally, between chemical scientists and
mathematical optimisation team, translating reaction needs into a
testable hypothesis, proof writings, as well as prototyping
pipelines that can be further developed and optimized by data
engineers and used by data scientists for machine learning.
1) Strong company vision and motive. I should know why I am doing it.
2) United and well-implemented company Culture system.  
3) Personal development Plan for workers. 
4) Working Pipeline of the company projects.
5) Understanding Team leaders.
6) No micro-management( A well-organised person usually tends to be distracted by micro-management, especially in a place where creativity and solution orientation is taking part.
Position: Senior Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: fluent

Successfully deliver to production:
* set up from scratch machine learning model deployment flow with CI.
* document categorization project with high amounts of models and Big Data;
* search recommendation improvement tool;
* sentiment analysis model;
* key-phrase retrieval project.
Data Scientist, with expertise in Natural Language Processing area and solid mathematical background. 
I have experience with:
•	solving low- and limited- resources problems;
•	working on big projects with high amount of models, and guide it from designing to delivering into production;
•	providing data and model insights.
My experience allows me to be both a researcher data scientist and connect conducted research for business needs.
I am an active DS community member, interesting in Explainable AI and Anomaly Detection.

Experience:
Working as a full-stack data scientist – communicate with customers, define requirements and data collection/labeling process, build and develop DS solution, deploy it as a ready-to-use service and communicate regarding integration with customers.
As well I has experienced in more engineering role, which involves setting up model deployment process, prepare machine learning services.
Working with rich data as pdf files, that have multiple modalities and developing complex models with structured outputs. Developing novel algorithms and working prototypes for information retrieval,  key phrase extraction from documents for multiple languages. Create solutions related to key phrase extraction, topic modelling, NER recognition,  text clustering and classification, documents similarities.
Flexible schedule, ability to work remote, the opportunity to grow and contribute to the community.
Position: Senior Data Scientist/Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: upper


Developed machine learning solutions in various contexts related to Computer vision, Tabular data, Time series, Digital signals processing, and more. Experienced in building efficient Machine learning pipelines and overall MLOps strategy, moving within the unclear scope of requirements, taking a leadership role, communicating with C-level stakeholders.

Last projects: 
Development of SOTA computer vision models optimized for mobile devices that work in real-time. 
Retail sales forecasting for massive variation of SKUs, stores, products

Certified AWS Machine Learning Engineer and Azure Data Scientist.
Position: Senior Data Scientist / Machine learning Engineer / NLP Engineer
Category: Data Science
Experience: 6 years | English: fluent


6+ experience in projects of NLP tasks(code generation, sentiment analysis, text summarization, classification), CV(Object Detection, GAN) scoring modeling, churn predictions;
Demand Forecasting,modern Time Series(TBATS, Pyramid Arima, Prophet, Holt-Winters, Hybrid CNN-LSTM, TCNs); 

NLP, Python, R language, Pandas, NumPy, scikit-learn, Keras, Tensorflow, PyTorch, XGBoost, LightGBM, CatBoost, Hyperopt, ensemble methods, NLTK, SpaCy, Gensim, BERT, Transformers 

I am a participant in different kinds of hackathons and Kaggle competitions.
I am looking for a long-term stable job with challenging projects.
Preferably NLP, CV domain.
Position: Senior Data Scientist / Machine Learning Engineer / Team Lead / Tech Lead
Category: Data Science
Experience: 6 years | English: fluent

- BS in Computer Science
- Built a data processing pipeline for automated receipt recognition. Utilized Computer Vision and NLP techniques for image and text processing, deployed models for prediction through REST APIs;
- Researched & developed a contextual AI assistant, from initial concept to a working prototype. Designed a process of data collection and labeling, utilized text classification and named entity recognition models for information extraction, and machine learning-based dialogue management;
- Built an AI-based Resume parser for En/Ru/Ua languages;
- Productionized a complex data pipeline for a Job marketplace with microservices using docker compose and bash scripts.
- Led a team of Computer Vision specialists in a startup where we created AI/AR version of the product utilizing Object Detection & Object Tracking ML solutions;
Business-oriented Data Scientist with 5 years of hands-on experience. Specialized in Natural Language Processing, Computer Vision, and Deep Learning.

Tech Skills:
- Python and it's scientific stack: Numpy, Pandas, Scikit-learn, Jupyter notebook
- Transformer, RNN, CNN architectures
- Deep Learning frameworks: PyTorch, TensorFlow, Keras, fastai
- NLP libraries: SpaCy, NLTK, Gensim, TextBlob, Transformers
- Cloud platforms: AWS, GCP, Paperspace
- Bash, Docker, SQL, Flask, REST APIs

Completed Projects in:
- NLP: Text/Document Classification, Named Entity Recognition, Text Summarization, Information Retrieval
- Computer Vision: Image Classification, Object Detection, Object Tracking, Semantic Segmentation
- Recommendation Systems: Collaborative filtering, Content-based filtering
Interested in a long-term full-time project related to Deep Learning. Preferably NLP, or some mixture of NLP with Computer Vision/Recommendation Systems.
Position: Senior Data Scientist / ML Engineer
Category: Data Science
Experience: 7 years | English: fluent

1. Kaggle Competitions Expert level.
2. A bunch of finished MOOC DS courses: 
- Ng's Deep Learning
- J.H.University Data Science Specialisation
- ODS open ML course
- CS-231n (Convolutional networks)
- HSE & Yandex ML basics
- Yandex's SHAD (Data Analysis School) courses
3. As I've said, I lecture at university (ML math basics course). In addition to deep intrusion into ML algorithms' basis, I try to help fresh students to get a bit more about their real future opportunities in industry, from the side of active specialist.
1. (currently) 6 months in Microsoft, Bing Core team, full-time remote. Improving SERP Question-and-Answering experience. EDA + ETL; Extract the most popular & intent queries from logs and push them through crowdsourcing. Use various SE / ML models to generate & check & filter queries / answers during data pipeline. Running A/B to prod. Built monitoring process for our QnA scenario.(business + data metrics). Used Python, SCOPE (internal SQL-like), Pytorch.
2. Two years at Yandex. Full-time office, Analyst, Researcher, fullstack DS/ML Engineer.  Created new product features using ML. I'm responsible for the whole feature development from gathering business desires up to micro-service deployment. Gathering & cleaning data, EDA, model selection & fitting, writing a production-ready code, model retraining, model-as-micro-service deployment, monitoring, logging. Used SQL, Docker, Python, Grafana, MR, internal Yandex tools.
3. (2020 spring) Lectures at university (ML math basics course) for master students. Prepared course plan, lecture presentations, homeworks, practice tasks. Lecture to students, give a seminars, check their homeworks etc. Main efforts are directed to math that different ML algorithms and methods are based on.
4. Two years in international startup (full-time remote). ML Engineer, Researcher, Analyst. Used Docker, Python, PostgreSQL, Flask. Built an MVP on analysing bitcoin blockchain structures
5. Two years as Software engineer
+ Fulltime remote team, business trips are adoptable
+ Small or medium team size, maybe startup
+ Diverse tasks: I feel myself much better as fullstack specialist
- Outsorce / outstaff: I prefer product companies
- Constant crunch / overtimes