Поиск вакансий

• A minimum of a Bachelor’s degree in a mathematical discipline such as Computer Science, Applied Statistics, Maths, Engineering, or Physics from a respected University. A Ph.D. is a bonus
• 4+ years experience in Python and good knowledge of R
• At least 4 years practical experience of univariate and multivariate statistical analysis in Python or R with large data sets (millions of records and many tens or hundreds of independent variables)
• Good experience of variable transformation and data preprocessing techniques to extract maximum predictive power such as binning, piecewise linear regression, non-linear function transforms, etc.
• Excellent practical knowledge of multi-variate techniques such as Logistic Regression, Decision Trees, Random Forest, Naive Bayes, Clustering, etc. and a good grasp of the strengths and weaknesses of specific approaches
• Strong communication skills

— 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.

● 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

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.