Data Engineering

— Experience with the following languages/frameworks: Python, C++; Pytorch / Tensorflow /Keras/ OpenCV;
— Advanced understanding and working experience of various fundamentals and concepts of computer vision
and machine learning;
— Good understanding of low level image processing, noise filtering, segmentation feature extraction/matching
techniques;
— Familiarity with architectures for classification tasks: CNN, Faster R-CNN, ResNet; detections: YOLO, HOG;
segmentation: U-Net, DeepLab, PSPNet;
— Previous direct experience of video analytics algorithm/system development for specific problems

• Advanced degree (Ph.D. preferred) in engineering, science, mathematics or related subjects
• Expert knowledge of statistical programming languages such as R or Python, and SQL.
• Readiness to work with engineering teams to develop prototypes of software products leveraging exploratory data analytics.
• Expert knowledge of data visualization, using tools such as Tableau or PowerBI.
• Expert knowledge of Experimental Design and Statistical Decision Theory.
• Solid knowledge of distributed data storage and computing, including Hadoop or Cassandra.
• Practical knowledge of cloud computing, including AWS (preferred) or Azure and highly scalable databases, such as Dynamo DB.
• Knowledge of NoSQL databases, such as MongoDB.
• Great communication skills in English.
• 5+ years working and communicating with business stakeholders as a trusted adviser in data science.
• 5+ years translating business requirements into data science problem statements and execution tasks.
• In-depth understanding of the machine learning lifecycle.
• Practical skills with agile software development methods such as Scrum and Kanban

With good theoretical and practical knowledge of the computer vision algorithms, neural networks, and deep learning in the field of computer vision (CNN, RNN, autoencoders, GAN)

Highly skilled in machine learning methods application

With an exceptional mathematical base (algebra, probability theory). Functional analysis proficiency will be a big advantage. Math faculties education is preferred

Python coding, Git , Ubuntu, DVC

Experienced in Keras, Tensorflow, PyTorch, OpenCV

Able to conduct research autonomously and proactively (incl. studying math articles and applying the knowledge in practice)

Striving to develop solutions completely new to the market, to the industry and to the world.

Experience in Machine Learning 1-2 years;
Practical skills with Deep Learning (TensorFlow / PyTorch / Keras) on similar media projects;
Good practice in CNN, frequency, GAN
Expertise in NLP (Natural Language Processing);
Desire to work in Security (Malware Analysis);
Previous skills in Python/Pandas, Redis, Git, RabbitMQ, JS/ CSS/HTML, JSON, Vanilla JS, AJAX, SQL/MySQL/PostgreSQL, PHP, Ruby, Ajax, API, Go, Java, C, C++ etc;
Excellent knowledge of web architecture & existing social media
DataScience skills will be an advantage
Higher technical education;
Technical English (higher level is advantage);
Hacking thinking is a must

(MLOps, ML, Data Analysis, Python, SQL, ETL, Visualization, Wiki)
Technical or Economics Degree
3+ years of corresponding experience
Experience with MLOps (preferably DVC, MLflow, Airflow, Flask, Docker, Git, etc.)
Strong Machine Learning and Data Analysis skills
Experience with ML frameworks (TensorFlow/Keras, etc.)
Strong Python and SQL
Experience with ETL and visualization tools
Good understanding of DWH & Data Lakes architecture
Good documentation skills
Intermediate English level or higher

• 2 years of commercial experience preferred;
• Extensive experience in Cloud technologies and tools such as AWS;
• Proficiency in the use of Python (Pandas, sklearn, numpy, TensorFlow or PyTorch);
• Extensive Data Analysis skills, Data Processing;
• Demonstrated proficiency in the use of SQL;
• Experience with Git;
• Experience with CI/CD.

MS or higher in the following areas: Statistics and Mathematics
At least 3-5 years of professional industry experience, in addition to your academic experience
Outstanding quantitative analytical ability
Able to take less than precise business requirements and translate them into logic problems which you enjoy solving
Independent and creative approach to problem solving
Excellent written and verbal communication skills, with prior experience explaining assumptions, conclusions and methodology to both internal and external customers
In-depth knowledge of Statistics/Probability/Machine Learning
General Statistical concepts such as hypothesis testing, estimation, inference
Supervised and unsupervised statistical techniques such as regression (linear / logistic), time series analysis, clustering
Machine Learning foundations such as bias/variance trade-off, regularization, dimension reduction
Real world experience with popular machine Learning algorithms such as Random Forest, Boosting, SVMs
Experience with unstructured text data using NLP methods such as Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA), Sentiment Models, Word Embeddings, Text Similarity, Entity extraction is a strong plus
Strong programming experience in Pyton and one of the following: Scala/Java, R
Understanding of algorithm complexity and performance implications
Knowledge of data structures and algorithms
Good knowledge of Knowledge Engineering
Good knowledge of Graph technology, Knowledge Graphs, Graph Data bases and Ontologies
Experience with SQL
Familiarity with R Shiny framework is a plus

Опыт работы: 3 года
Data Scientist - 3 года
Опыт в Python
Опыт в PySpark
Опыт в NLP

• 3+ years of experience as a data scientist.
• Experience in defining and implementing feature engineering processes for ML based products
• Experience in writing code in Python (and Pyspark) and using Python data-science frameworks.
• BSc/BA in Mathematics, Physics, Computer Science, Economics, or another related field.
• Experience with building solutions with Big Data tools and frameworks such as Spark, Hadoop, etc.
• Experience in developing machine learning oriented solutions for the financial sector - advantage
• Experienced with machine learning framework such as Sklearn - a must, TensorFlow/Keras - advantage
• Experience with NLP - an advantage.
• Experience with Graph Algorithms - an advantage.
• Great communication skills.
• Ability to quickly learn new technologies, frameworks, and algorithms.
• Very good English, written and verbal.

— Technologies:
Mediapipe framework (Skeleton models and behavior recognition)
yolov5
CNNs
Torch
Python
OpenCV
Experience with models on edge devices

— Experience:
2+ years in CV applications;
previous experience in building high load computer vision applications;
previous experience in training and deploying of light models on EDGE device;
models distillation.