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Hola Amigo! Do you think you have an analytical mindset and knack for cracking data codes to orchestrate a compelling story, then you have what it takes to be a data analyst or a data scientist. If still not excited by your own ability, then the recent judgement of Harvard Business Review may delight you because it stated that the title of “data scientist” is the “sexiest job of the 21st century”. Yes, this is the reason that data analytics jobs are in such high demand nowadays. One of the reports stated that the number of data analytics job listings are likely to grow multiple times in the next 2-3 years to reach approximately 2,720,000 by the year 2020. However, there is some confusion, even among people who have some basic knowledge of data science, about the role of data scientist and data analyst and how they differ from each other. Although, both work with data, but there are subtle differences in their roles and responsibilities and that is what we will discuss in this article (based on knowledge shared by my friends). So, let us note down some of the keys differences between a data analyst and a data scientist.

What do they do

Data Analyst: One of my friend, Ajay, is working with an MNC bank as a data analyst. So, his role is to study large data sets and try to draw some insights in order to identify patterns, create charts and build visual presentations to help senior management in making strategic decisions.

Data Scientist: Another friend of mine, Richa, is also working with an MNC bank, but as a data scientist. Her role is a little different than that of Ajay, as she is more into designing and constructing new processes for data modelling. Further, she is also responsible for the development of algorithms, prototypes, predictive models and custom analysis. She uses a variety of data analysis techniques such as data mining and machine learning.

what are the qualifications required

Data Analyst: Ajay is an undergraduate with an engineering degree which is adequate for his current role. A typical data analyst is required to have an undergraduate degree in science, technology, engineering, or math, while an advanced degree is just a “nice to have,” but not at all mandatory. However, you must know that Ajay has strong skills in science, math, databases, programming, modelling and predictive analytics.

Other core skills that a typical data analyst should have include:

  • Experience of working with different computer languages such as SQL, R, Python etc.
  • Combination of intellectual curiosity and analytical skills
  • Strong grasp of data mining techniques
  • Strong awareness and intent for upcoming technology such as agile methodology
  • Strong written and verbal communication skills

Data Scientist: Well to be a data scientist, you need to work a little harder to build your educational background. Statistically, nearly 90% of the data scientists have advanced degrees, which is further vindicated by another survey report that found nearly 88% of the data scientists have a master’s degree and 46% have a PhD. So, Richa is no exception to the findings as she holds a master’s degree in computer science.

Other core skills that a typical data scientist should have include:

  • Experience of working with computer languages such as R, Python, SQL, etc.
  • Experience in data mining techniques such as generalized linear model, regression, random forest, text mining etc.
  • Working knowledge of data architecture creation and statistical model building
  • Strong understanding of machine learning techniques including, decision tree learning, clustering and artificial neural networks
  • Experience of working with web services, distributed data/computing tools and analysing data for third-party service providers
  • Strong presentation skills required to produce business cases to stakeholders

what are their responsibilities

Data Analyst: When Ajay was asked about his responsibilities, he told that as a data analyst he is required to constantly analyse data and interpret the patterns exhibited by them. Further, he added that their focus on programming skills is slightly less than that of a data scientist. He said that his core responsibilities include:

  • Conduct research and analytics on consumer data
  • Prepare tailor-made customer-centric algorithm models for each client
  • Draw logical insights from large databases
  • Support day-to-day decision making by performing quantitative analysis
  • Translation of data into visual metrics
  • Create SQL queries for data extraction from the data warehouse

Data Scientist: When Richa was asked the same question, she told that as a data scientist she is required to run data science projects from end to end that includes storage and cleaning of a large amount of data, exploration of data sets for identifying logical insights, building predictive models and then finally present a story capturing all the findings. She said that her core responsibilities include:

  • Mining and analysis of data to improve product development, marketing techniques and business strategies of the client
  • Use of predictive modelling to enhance customer experience intended for higher revenue generation of the client
  • Develop customized data models and algorithms, and create tools to monitor model performance and data accuracy
  • Develop processes to assess the effectiveness and accuracy of new data sources
  • Co-ordinate with other functional teams for smooth model implementation

how much do they earn

Data Analyst: Well, honestly speaking I couldn’t ask Ajay about his salary. Nevertheless, I will give you some idea based on available market data that stated that remuneration of a data analyst can be anything in the range of $80,00-$120,000. Further, a data analyst can also boost his paycheck by learning additional programming skills.

Data Scientist: Same goes for Richa too and so again based on market data – since these professionals are having advanced degrees and skill sets with more experience, as such, they are able to draw higher compensation. Based on available data, it is estimated that a data scientist can land a job with remuneration in the range of $115,000-$165,000.

conclusion

So, it can be concluded that the job titles of a data analyst and a data scientist are deceptively similar, but they can be distinguished based on educational requirement, job responsibility and career path. Interestingly, there are many data scientists who actually started their career as a data analyst and later became a data scientist. Nevertheless, you can opt for either of the career choices given that qualified individuals from both categories are highly coveted in today’s job market.