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Junior Data Scientist


Industry: Information Technologies

City: Yerevan

Employment type: Full time

Deadline: 12/17/2021


Junior Data Scientist will work closely with our data science team on implementing bleeding-edge machine learning methods. The ideal candidate should have a strong academic background in ML and excellent programming abilities, preferably in Python.


  • Apply NLP algorithms to extract information or insight from raw text data.
  • Apply image recognition algorithms to help enrich data and improve data quality.
  • Develop tools or libraries to enhance and automate data science workflow.
  • Receives general supervision and guidance from more experienced team members.
  • Follows department processes, procedures and client requirements; may make recommendations and/or implement improvements/ solutions.
  • Provide general administrative support as needed.
  • Participate in special projects and perform other duties as required.


  • Be working towards a BS or MS degree in Data Science, Statistics, Analytics, Computer Science, Information Systems, or a related degree.
  • Basic analysis skills; familiar with data analysis tools and techniques, such as Python, R, text analytics, NLP.
  • Familiar with SQL in the extraction and manipulation of datasets.
  • Experience in Labeled Property Graph Databases (e.g. Neo4J, TigerGraph, AWS Neptune, Azure Cosmos DB, or similar) and Graph query languages (e.g. Gremlin, SPARQL, Cypher, or similar) will be a great plus.
  • Able to manage and integrate insights and establish monitoring around multiple internal data sources.
  • Ingestion, standardization, metadata management, business rule curation, data enhancement, and statistical computation against data sources that include relational, XML, JSON, streaming, REST API, and unstructured data.
  • Experience and interest in presenting analytic findings to business customers. Familiar with reporting and visualization tools, such as Tableau, Power BI, Business Objects, etc.
  • Experience and interest in deeper analysis of data subjects, potentially spanning over a timeline of several months.