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Data scientist

Data scientist
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Data scientist
Data scientist
Resume examples
Resume Examples Objectives and summaries Templates

9Data scientist resume examples found

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Computer science resume examples
Data scientist Computer scientist Machine learning specialist
Experience level
Entry level Experienced Senior

Data scientist

Entry level

Tasked with transferring data into new formats to make the information more appropriate for analysis. Built analytical tools to automate the data collection process and decrease the amount of time for reporting and suggesting technological advancements and/or changes.

  • Created and improved computer software and hardware under the direct supervision of the lead data scientist and computer engineers.
  • Helped develop streamlined algorithms to reduce the amount of processing time and make computer tasks more efficient.
  • Tested scalable schema designs, relational database, query performance, workflow optimization, and documentation.
  • Developed significant and concise analytic objectives according to business goals and initiatives and under the guidance of department supervisors.
  • Designed and built interactive dashboards, machine learning models, and innovative analytics tools using a variety of programming languages.
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Data scientist

Entry level

Searched through large data sets for useful information to assist in the business decision-making process as directed by the lead data analyst and other key stakeholders. Demonstrated persistence, statistical, and engineering capabilities necessary in understanding biases and inconsistencies in data.

  • Tasked to establish methodologies to improve algorithms to allow advancements in machine learning and cloud computing systems.
  • Helped design new computer architectures to improve performance, effectiveness, and efficiency in computer software and hardware.
  • Executed and troubleshot analysis workflow while maintaining excellent and comprehensive written records of activities.
  • Collaborated effectively between the business department and data groups, by paying meticulous attention to detail and differentiating communication and presentation skills.
  • Performed data exploration to understand end-user behavior and identify opportunities for improving software features.
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