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Data Scientist

POSITION SUMMARY

Data Scientists create value from data. They obtain information from various sources and analyze it to gain a better understanding of how a business performs. In order to increase efficiency within a business, Data Scientists can build Artificial Intelligence (AI) tools to automate certain parts.

Data Scientists can perform a myriad of job functions including the creation of various machine learning tools or processes within the business. They sometimes work with third party sources to verify businesses’ data and then create automated detection systems in order to stay on top of data tracking efforts.

RESPONSIBILITIES

Data Scientist responsibilities may include:

  • Data mining using industry best practices.
  • Augment existing data collection databases.
  • Build classifiers using machine learning techniques.
  • Create automated tracking systems.
  • Verify the integrity of data used for analysis.

 

SKILLS

Data Scientists are essential in gathering data about an organization or industry. In order to obtain useful information and utilize it effectively, a skilled Data Scientist will:

  • Possess a strong work ethic needed to carefully examine large amounts of data.
  • Possess an eye for detail to catch inaccuracies and outliers.
  • Communicate clearly with staff members and senior members alike.
  • Compile information into identifiable documentation.
  • Possess organizational skills to stay on top competing priorities.


QUALIFICATIONS

Most positions as a Data Scientist require applicants to possess a Master’s Degree in mathematics, computer science, or a related field. However, it is not uncommon for Data Scientists to possess Doctorates. 

Candidates may also obtain additional certification or go through advanced learning courses to further differentiate themselves within the field.

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DATA SCIENTIST INTERVIEW QUESTIONS

  • While compiling a report for user content uploads, you notice a spike in September. What do you think may have caused this?

  • Can you explain what data leakage is, as it pertains to machine learning?

  • How can you test that a feedback survey was filled out randomly or truthfully by customers?

  • How do you calculate variance in an unsupervised model?

  • Why is ensuring that data is secured so important?

  • Name one way that data could change the world.

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