Data Engineering

— At least 2 year of commercial experience in DS;
— Strong knowledge of linear algebra, calculus, statistics and probability theory;
— Knowledge and experience with algorithms and data structures;
— Strong knowledge of Python (numpy, pandas, scikit-learn, etc.);
— Experience in Natural Language Processing;
— Hands-on experience in statistical analysis, regression, classification, topic modelling, time series, predictive modeling;
— Experience with SQL;
— Knowledge of OOP;
— At least Upper-Intermediate (written and spoken) level of English.

Higher education in statistics, computer science, mathematics or applied physics program;
2+ years of professional experience in data science environment utilizing quantitative analytics methodologies;
Proficiency in at least one statistical software package such as R, other will be considered as advantage;
Expertise using SQL for acquiring and transforming data;
Outstanding quantitative modeling and statistical analysis skills;;
Good communication skills in English and Russian;

Ability to write code in Python.
Strong algorithmic skills.
Basic knowledge and practical experience of Machine Learning.
Knowledge of Machine Learning-related math (linear algebra, probability theory, etc.).
Basic knowledge of software architecture design.
Active involvement and interest in Machine Learning.
Experience with some Machine Learning-related libraries, such as NumPy, Matplotlib, NLTK, Pandas, SkiPy and others.
Communication skills.

Знания в области машинного обучения, интеллектуального анализа данных
Знания математической статистики и теории вероятности
Опыт разработки ML- моделей на Python не менее 6 мес.
Владение SQL

● Professional data engineering experience focused on batch and real-time data pipelines using Spark, PySpark, Python (Scala is a plus).
● Strong hands-on working experience of Big Data stack including Spark and Python(Pandas is a plus).
● Awareness of DevOps.
● Hands-on design and development experience in data space: data processing/data transformation using ETL tools, a data warehouse (data modeling, programming).
● Exposure to Google Cloud and Amazon Web Services.
● Experience working in a high load / high performance distributed project.
● Experience both with async code and with multithreading/multiprocessing.
● Hands-on experience with SQL (e.g. PostgreSQL) and NoSQL databases (MongoDB, Redis, Elasticsearch, etc.)
● An open-minded person who is willing to work in a dynamic R&D environment.

— Experience in one of Python, Java or Scala
— Experience in implementation of Machine Learning
— Experience with developing dashboards and reports
— Strong SQL skills (MySQL, PostgreSQL)
— Knowledge of working with large datasets
— Strong technical, analytical, and mathematical skills
— Intermediate English or higher

Strong mathematical background, keen sense of complexity estimation, a
paranoia for writing efficient code.

• Masters in Computer Science or related branches with 2+ years of
  experience in industry.
• Very strong linear algebra fundamentals.
• Reasonable DSP skills.
• Experience with supervised as well as unsupervised learning
  algorithms.
• Most importantly, the ability to connect the usage scenarios of a system
  with it's basic specifications.
• The flexibility to feel at home in a technology start-up with a small team
  that demonstrates adaptability to fast changing needs.

• Hands-on experience (3-6 years) developing machine learning solutions with Python for Unstructured Text Based Problems (NLP), including: ML problem analysis, Data preparation (Exploratory Data Analysis) & transformation, Feature analysis & selection, Topic Modelling & NER (Named Entity Recognition), ML model selection using parameter tuning, Model result analysis and presentation, Transfer Learning, Developing custom ML Model based on requirement
• Good knowledge of machine learning libraries (like Scikit-learn, NLTK, spacy etc.)
• Strong programming knowledge in Python, Flask, NumPy, Pandas etc.
• Good knowledge in statistics and algorithms
• Experience in image recognition or OCR technology
• English level: Intermediate.

-4+ years of successful data science experience
-Experience with/good knowledge of NLP, pattern recognition, deep learning and other ML technologies
-Excellent programming skills, expert in Python/Java/R
-Degree in Math / Statistics / Physics

Розуміння концепцій статистики /теорії ймовірності, аналізу даних, машинного навчання
Знання мов програмування SQL, Python\R
Вміння будувати змістовні візуалізації результатів
Вміння створювати і підтримувати документацію про створені моделі і процеси
Відмінне розуміння методів машинного навчання та алгоритмів, таких як k-NN, Naive Bayes, SVM, Decision Forests, NN etc
Досвід роботи на позиції Data Scientist від 2х років
Досвід створення та впровадження повного циклу ML моделей (from research to production)
Досвід використання поширених DS інструментаріїв (numpy, scipy, pandas, sklearn, xgboost, etc.)