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Must-have:

• MSc/BSc in Computer Science or similar degree. Knowledge of statistics, probability theory and linear algebra.
• Good knowledge of ML theory and practice — pros & cons of different model types, validation, metrics, hyperparameter tuning, interpretability
• Experience with Tensorflow and Keras (can implement custom NN model from paper)
• Practical experience with ML models in production (2+ years)
• Experience with distributed model training and distributed feature engineering (Spark/Dask/Apache Beam)
• Python 3.х, software engineering skills (able to produce well-structured production-level projects, not only notebook scripts)


Must-have:
  • MS degree in Computer Science or other related fields
  • 3+ years of coding experience with Python
  • A proven track record of R&D projects in ML and/or CV
  • Advanced knowledge and experience in methods for the analysis of time-series data
  • Deep knowledge of such packages as Numpy, Scikit-Learn, Matplotlib, Kats, Sktime
  • SQL Databases + Snowflake
  • Upper-intermediate English
  • Proactivity and good soft skills

Must-have:

Have a PhD or Masters in Computer Vision, Computer Science, or related field
Be passionate about creating innovative techniques, and making them robust and scalable
Have (at least) 4 years of experience in applying state-of-the-art Computer Vision and Machine methods on industrial applications
Be autonomous, a team player with a positive mindset
Be creative and innovation-focused
Excellent communication skills in English and ability to effectively communicate complex technical concepts
Broad expertise in Computer Vision and Machine Learning (e.g., object detection, tracking, segmentation, image classification, 3D reconstruction, image and video processing, graphics rendering, etc.)
Solid programming skills with Python and/or C/C++
Previous experience in Tensorflow and/or Pytorch


Must-have:
  • 5+ years of relevant experience with a proven track record of developing algorithms and machine learning products for production ready recommendation or prediction systems using languages and big data platforms such as Scala, Python, R, Java, Spark, Cassandra, and Hadoop.
  • Deep understanding and experience in Big Data concepts
  • Extensive knowledge of ML frameworks, libraries (e.g. Scikit, Numpy, Pandas, TensorFlow, R ML packages), tools (AWS EMR, Databricks, Knime, etc), data structures, data modeling concepts
  • Able to organize and architect ML modules
  • In-depth knowledge of mathematics, statistics, and algorithms (Random Forests, General Linear Regression, Elastic Nets, Clustering, and NLP)
  • Superb analytical and problem-solving abilities
  • Great communication, collaboration skills, time management and organizational abilities
  • BS/MS in Computer Science, ML, Mathematics, or related field and/or equivalent work experience

Must-have:

Programming experience in Python/Matlab
AWS SageMaker - huge plus
Experience of 4+ years in data science working in a production environment
Strong English and communication skills (both speech and writing)
Highly motivated and positive-attituded person
Team player
Experience with agile development methodology
Outstanding communication skills
Passion for data
Delivery oriented
Experience with Java
Experience with Signal Processing
Experience in the field of predictive maintenance
Data science
Machine learning algorithms
Data engineering
Deep learning
CS algorithms
Python /Matlab
Signal processing


Must-have:
  • 8-12 years of working experience, specifically with SQL databases
  • Solid experience with R
  • Experience in Python (scikit-learn package)
  • Experience in handling and processing large multi-modal datasets (labs/vitals/reports/images)
  • Experience in the management and handling of high frequently measured datasets (e.g. via indexing in SQL databases)
  • Joining of multiple / diverse data frames
  • Experience in creating informative descriptive statistics of high-dimensional datasets (medians, means, missingness etc.)
  • Experience in analyzing longitudinal / time series data
  • Experience in the development, validation and interpretation of machine learning models. E.g. Random Forest, Boosted Trees, Regularized Logistic - Regression. Cross-validation, Up- & Down sampling
  • English - upper-intermediate

Must-have:

Опыт работы на позиции DS от 1 года.
Хороше знание Python. Использование пакетов numpy, pandas, scikit-learn итд.
Математический бэкграунд
Понимание основных принципов и техник в машинном обучении, supervised и unsupervised learning
Знание методов предобработки данных
Знание методов и инструментов ETL и инструментов визуализации
Понимание алгоритмов, структур данных
Опыт с нейронными сетями, работа с текстами, звуком и изображениями
Релевантный опыт с SQL и NoSQL базами данных
Разработка на Flask, внедрение собственных моделей в прод
Знание инфраструктуры и инструментов на GC, AWS, Azure
Опыт организации Data Lake/Data Mesh, описания метаданных, разворачивания инфраструктуры (MS Azure prefered).


Must-have:
  • Strong mathematical background
  • Experience with NLP
  • Knowledge of state-of-the-art DL libraries
  • Knowledge of Python (pandas, numpy, scipy, nltk, spacy)
  • Ability to communicate in English on technical topics

Must-have:

● A bachelor's degree in statistics, math, computer science, or
engineering.
● 3+ years of ML experience.
● Experienced at Python3.
● Strong problem-solving skills with an emphasis on product development.
● Proven experience in industrial production projects.
● The ability to work on several projects in parallel.


Must-have:
  • Statistics collection from large data sets (Spark, Data Analysis)
  • Building Predictive models based on data in Oil Industry Field (Spark, Machine Learning)
  • Analyze data in order to target business goals like costs or risks reduction (Spark, Data Analysis, Data Mining)
  • Distributed data computation (Spark)
    Mandatory Skills Description:
    C++/Python
    Apache Spark
    Data Engineering,
    SQL