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.
-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