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Data Analyst

POSITION SUMMARY

Data Analysts translate data into information, information into insight, and insight into practical solutions. This data may be used in countless ways from determining how to reduce costs for transportation, produce new materials, or solve staffing issues that cost the company money. 

Data Analysts can specialize in many fields, including that of operations, finance, and marketing. They possess skills that can be used in other aspects of Information Technology and are necessary to provide business leaders with insight.

RESPONSIBILITIES

Data Analyst responsibilities may include:

  • Acquire data from primary and secondary data sources.
  • Cleansing data to ensure that it is in the proper format.
  • Interpret data to look for trends.
  • Conducting life cycle analysis.
  • Develop new process improvements based on discoveries.
  • Filter data to correct code problems.


SKILLS

Data Analysts are essential to providing management with valuable insights into company data. In order to best utilize that information, a skilled Data Analyst will:

  • Possess an eye for detail in order to identify code problems.
  • Be able to translate technical data into layman’s terms.
  • Possess superior interpersonal skills to maintain pleasant working relationships.
  • Have strong organization and prioritization skills to manage large sets of data.
  • Utilize creative thinking to provide revolutionary business insight.

 

QUALIFICATIONS

In order to secure an entry level position, candidates will need to possess a Bachelor’s Degree in Mathematics, Computer Science, or a related field. Certification is available for Analysts wishing to specialize in a certain area.

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DATA ANALYST INTERVIEW QUESTIONS

  • What experience do you have with qualitative data?

  • How would you define data cleaning?

  • How do you fix an anomaly or outlier in a dataset?

  • How often should you retrain a data model?

  • What is your experience in data reconciliation?

  • Name a few methods you have used when data cleansing.

  • Describe some common problems found in data analysis.

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