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Big Data Engineer

Remote

Locations: excl. Belarus, Russia.

Job Type

Full Time

Status

Closed

About the Customer

The Customer provides business data enrichment with unprecedented coverage of private companies, accurate classification and in-depth insights based on real-time updates, for procurement, insurance, market intelligence and more.

About the Project

We are seeking a Big Data Developer to join our friendly team of experts. Your mission will be to improve the overall quality, width and depth of the data collected on companies worldwide.

Responsibilities

  • Mine and analyze data from across the web

  • Assess the effectiveness and accuracy of new data sources and data gathering techniques

  • Develop custom data models and algorithms to apply to text datasets

  • Use predictive modeling to increase and optimize data extraction and data quality at ingestion and post-processing

  • Develop the company's A/B data testing framework and test the quality of the data continuously

  • Develop processes and tools to monitor and analyze model performance and data accuracy.

  • Prototype quickly to solve thorny use cases, without getting stuck in theory, as we're prone to shipping early and often

  • Write well-designed, testable, efficient code

  • Identify areas of opportunity and improvement

Requirements

  • Experience using statistical computer languages, preferably Scala (or R, Python, SQL, etc.) to manipulate data and draw insights from (very!) large data sets

  • Expertise working with and creating data architectures (Spark, Cassandra)

  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

  • High speed and uncompromising quality in your work

  • A growth mindset, able to capitalize on unprecedented contexts through your skills and abilities

  • An appetite to grapple with a variety of technical challenges

  • The ability to quickly and effectively evaluate technical tradeoffs and translate them into relevant scenarios

Nice to Have:

  • Any knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks etc.) and their real-world advantages/drawbacks

English level:

  • Intermediate+

Job Application Form
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Thank you! We'll get in touch soon.

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