What They Are - How To Get The job

Data science professionals have gained significance immensely over the years, and this is not without a reason. The ocean of data can seem to be absurd until it is converted into insightful, meaningful information. Data scientists work on a broad spectrum. It can be anything to do with the new range of medications for a virus or serious security threats at the borders. A data scientist needs to combine various skills that include- modelling, statistics, computer science, analytics and critical skills. What the data scientists bring out from the sea of data becomes the actionable objective of organizations.
 
The data scientists design the process of data modelling. They create the algorithm and predict the models. Performing custom analysis is also a part of the responsibilities of these professionals. A data scientist works at the mid-management level. He or she has to analyse and monitor the associates who do a variety of tasks. When dealing with the niche of data science, the task begins with cleaning and aggregating data and transferring it to the data warehouses from multiple sources. The data is later analysed to find the trends and the organizations look forward to arriving at meaningful objectives as a result.
 
Here is the summary of the role of a data scientist in an ideal organization:
 
  • Collecting data, pre-processing the same before analysing it
  • Building models and using it to address the different problems faced by a business
  • Automate the data collection process after identifying the different sources
  • Discovering the trends and patterns after analysing the huge amount of data
  • Building models that are predictive along with machine-learning algorithms
  • Using ensemble modelling by combining the models
  • Using data visualization techniques
  • Proposing solutions and strategies to the challenges faced by the business
  • Collaborating with the different teams to get the best out of the segregated data
     
Different Types of Data Scientists:
 
Data science, as we see it today, is a relatively newer field. Hence, there are rapid changes in this field every day. However, there are a few categories of people in the field such as –
 
  • Generalists: These data scientists know a bit about everything and can manage to take care of teams where the roles keep changing or shifting. They are versatile and can even take care of a wide range of responsibilities single-handedly in small organizations.
  • Dabblers: A software engineer or a product manager might be required to play the role of a data scientist at some point of time. Such professionals who act as data scientists at least 25% of the day are called dabblers. They are well suited in organizations where technical knowledge can help to deal with the data.
  • ML Engineers: These are professionals who have a basic idea about statistics and software engineering and have enough expertise in model development. A few organizations or businesses have a lot more to do with model deployment, and these engineers fit in such businesses, where the model is what the business is all about.
  • Statisticians: In a few businesses, the dataset relevant to finance is used frequently. The statisticians are sound in this niche and are great resources here.
  • DS Managers: Professionals who know in and out of all these or majority of these responsibilities are suitable for positions that deal with team productivity, tooling and roadblock removing including a lot more tasks.
     
There are other roles of data scientists in various organizations and there are specific tasks required in specific organizations.
 
How to create a good profile for a data scientist?
 
The opportunities for data scientists are enormous but there are also numerous professionals eyeing the best jobs. It is essential that you create a profile with the following data, to ensure you catch the attention of the employer at the very first attempt –
 
  • Your qualification should be explained in brief.
  • Details about the courses or certifications completed in data science
  • Your technical skills that include programming knowledge, languages known, like C++, Java, and basic computer skills
  • Experience relevant to this field
  • Endorsements from previous employers
  • Additional qualifications like diploma or certification in statistics, finance, and data management. Even if you have completed a short course online, consider adding it to your resume. It will help employers understand your complete skillset.
     
The skills you need to own to become a good data scientist:
A few skill sets are mandatory if you want to grow in your chosen career of data science.
 
  • A master’s degree in social science, computer science, statistics, mathematics, or physical science is desired to become data scientist. Many data scientists even own a doctorate in common subjects, which is an added advantage.
  • Training to handle data querying like Hadoop. This is again an added advantage to ensure you grow as a data scientist
  • In-depth knowledge of analytical tools. R programming knowledge is considered to be the best solution to solve any problem. Knowledge of it is a must.
  • Knowledge and understanding of Python coding, Hadoop platform, SQL database coding, Apache Spark
  • Basic understanding of machine learning and AI. This gives you an advantage over the other aspirants. This is because the application of machine learning is often needed as a data scientist. He or she needs to deal with large amount of datasets and machine learning makes it easy for the professional to carry on their tasks.
  • Ability to visualize the data. Data visualization allows working with the data directly, and basic knowledge about data visualization tools like ggplot, Tableau helps as well.
  • Ability to work with unstructured data as well
  • Critical and innovative thinking, which helps in problem-solving
  • Effective verbal and written communication skills
  • You should also develop the ability to effectively work in a team since most business, both small and big, are now starting to hire teams of data scientists.
It is easy to achieve success as a data scientist when you work towards achieving these skills. Keeping yourself updated about the trends of the career is also key to be a successful data scientist.
 
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