Everyone wants to become a data scientist, after all, it is considered and labelled as the ‘sexiest job of the 21st century!’ There is a lot of mystic in the tile ‘Data Scientist’. The data scientist is considered as a wizard, with mystical skills, which when applied can get great insights from the existing data, that holds the key to the future success.
But as much as we would like to believe otherwise, it is the way the data is interpreted, analyzed and methods of data science applied by the data scientist that gets us great results. In this blog let's understand "What Does a Data Scientist Do?"
The power of data comes from great knowledge of Business Domain, Statistics, Algorithms, Computer Science or Programming skills and exceptional Communication Skills. These become the four pillars of data science. When these skills are applied in a harmonious and synchronized manner, the true essence of data science is discovered.
With the arrival of Big Data, comes the age of large datasets which cannot be managed by the traditional data processing applications. This has opened a way for skilled professionals who can do the job. A data scientist takes the raw data and analysis it in a way that makes it accessible and valuable for the organization to make strategic decisions.
So, in short, they analyze data to get actionable insights from it. A data scientist’s level of experience and knowledge would range from nascent to expert levels, and their degree of work will change with time and business requirements.
Precise tasks performed by the data scientist would be……
- Applying knowledge in identifying the best data analytics program suitable for the organization to optimise opportunities.
- Collecting and analysing large sets of data, in structured, unstructured and semi structured format.
- A major role of the data scientist would include cleaning, and mining and validating the sets of data to ensure that it is accurate, complete, correct and that it is uniform in nature.
- A data scientist has to ensure that the correct dataset and variables are defined.
- A data scientist would need to dedicate a great deal of time in applying models and algorithms to mine the stores of big data for insights.
- One of the key tasks of a data scientist is to identify the patterns and trends in the data set and communicate the same so that strategic decisions can be based on it.
- As much as they are required to identify trends, a data scientist jobs also require finding hidden solutions and opportunities from the data set.
- Lastly, use their communication and visualisations skills to translate the finding or while making suggestions to the stakeholders.
To perform the above tasks, it is vital to have knowledge in maths or statistics, an inquisitive mindset with critical thinking capabilities is an added advantage. A knack for connecting the dots, correlating findings from the data to business advantage is a must.
If you have a background in computer programing, it will be easier for you to devise the algorithms for excavating the stores of big data. R, Python, SAS, Hadoop are a few preferences. A business acumen, that like an entrepreneur will be a big advantage, as you need to be a leader in devising your own methods and building your own infrastructure so that you can treat the data in your own methods to get new discoveries from the same data sets.
Lastly, you need to be confident, understand the business domain of the institution you are working with. Possess exceptional communications skills to that you can explain technical findings to the non-technical stakeholders’.
Harvard correctly states Data scientist as the trendiest job, it is an extremely important role, high in demand and has a significant impact on business’s ability to achieve its goals irrespective of its nature.
