Who is a data scientist?

Data Science, AI and ML
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#1
A data scientist is an analytical expert who has the perfect mix of computer science, statistics as well as business acumen to convert complicated & intricate business problems into technical & statistical solutions which can enable business to use historical data to shape future decisions. In addition to that, a data scientist needs to also possess the requisite exploratory skills & curiosity to find potential risks & faults from data; and prescribe the most optimal solution to the business.




Furthermore, the precise definition of data scientist is not a rigid one and varies from businesses to businesses. A data scientist in one company could be doing a different set of jobs as compared to other businesses. Data science being a subset of machine learning; different ML profiles such as AI engineers etc. also at times come under the data scientist profile.

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#2

Data Scientists are the analytical experts who utilize their skills and analyze large sets of unstructured as well as structured data. Data scientists apply a strong data foundation to analyze and solve problems.

Data scientists work closely with industry experts to understand their goals and check how data can help them to achieve their goals. Data scientists use different data science techniques like machine learning and statistical modelling to measure results.

Skills required to become a data scientist :

  1. Programming
  2. Machine Learning techniques
  3. Data Visualization and Reporting
  4. Risk Analysis
  5. Statistical Analysis
  6. Data Mining
  7. Research
  8. Cloud Tools

Specialization

Data scientists can specialize in a particular industry or can develop skills in areas such as machine learning and artificial intelligence. Specialization is the best way to increase your potential and create a better future for yourself. InsideAIML is one of the best platforms that offer specialization in Data Science, Machine Learning and Artificial Intelligence. While researching for specialization you must consider InsideAIML.