Data Science in EpicentrK

Requirements:

Master's/Bachelor's degree in economics, statistics, data processing, intelligent data analysis, computer science

Practical experience of working with classical machine learning toolsets (linear models, classifications, clustering, dimensionality reduction), understanding of recommender systems (collaborative filtering, content base, hybrid), natural language processing (Transformers, fasttext, seq2seq, nltk ), deep learning (keras, pytorch, tensorflow, mxnet), and even running machine learning models in production environments.

Familiarity with at least server technologies

Ability to use SQL and NoSQL for queries to large databases and the ability to create and maintain processes to extract and integrate data from various sources.

Experience with statistical analysis tools such as Python (pandas, numpy, plotly, sklearn and other libraries)

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knowledge of mathematical statistics and probability theory

Additionally:

Business analytics tools

BigData stack (Clickhouse, Kafka, Hadoop, Spark)

ElasticSearch

ETL pipelines

Tasks:

Building, improving and support for ML models.

Determining the economic efficiency of the implemented model

Solve difficult tasks based on a large amount of data

Search for new ways to implement initiatives

Conducting A/B tests

intelligent data analysis