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A career in Data Science

Data Science is one of the hottest, trending and a growing field in IT sector. We all listen that Data science is going to change the world. The proper skills can make a Data Scientist change the world. If you are thinking of building a career in Data Science, there are a few important points you should know first. This blog will give you a clear idea about everything that you need to know before you start a career in Data Science.

Sometimes, you hear data scientists shoot a dozen of algorithms while discussing their experiments. You might think that there is no way a layman can master Data Science. It may sound as another mystery of the universe. But at the same time, you hear about urgent necessity to become a data-driven person and how it is advancing day by day.

In the last couple of years, the role as Data scientists has been deemed the “sexiest job of the 21st Century”.

As a beginner, you must be curious to learn it and become a tech guy with one of the Sexiest Job Title. At the same time, you might be having a lot of questions in your mind, for example:

  • What is Data Science?
  • The kind of skills you need to have?
  • The kind of Job roles you may get?

The path below leads you to the answers to all those questions

A career in Data Science
Few top skills beginners should be focusing on to start their career in Data Science

What is Data Science?

It is the area of study which involves extracting insights from vast amounts of data by the use of various scientific methods, algorithms and process. Therefore, we have to extract knowledge and useful information from huge volumes of Data.

After listening data these many times, you may find yourself asking, “which kind of data are we referring to?”. Well, the first thing to understand is that all data created are not equivalent. The data generated from social media apps (unstructured data) are completely different from the data(structured data) generated by point-of-sales or supply chain systems. Hence, Some data is structured, or semi structured, or semi-structured but most is unstructured. Today, only 21% of the data is present in structured but most are unstructured.

What skills do you need to have?

Regardless of your previous experience or skills, there exists a path for you to pursue a career in data science. To pursue a career in Data Science, you need some below-listed skills:

  • Business Intelligence:

You need not be an expert BA, what you need is to have clear ideas of the following:

  • Find and collect relevant data that exists for your area of interest and might answer your question
  • Analyse your data with selected tools
  • Look at your analysis and try to try to interpret findings.
  • Have a question or something you’re curious about

  • Programming Skills:

No matter what type of company or role you’re interviewing for, you’re likely going to be expected to know about these tools. This means a statistical programming language, like R or Python, and a database querying language like SQL is a must.

  • Statistics and Probability

A good understanding of statistics and probability is vital as a data scientist. Statistics means, the use of mathematics to perform technical analysis of data and to make estimates for further analysis. The methods of Statistics themselves are dependent on the theory of probability, which allows making predictions.

  • Machine Learning Algorithms:

When you are working at a company (like Netflix, Google Maps) where the product itself is data-driven; you will have to be familiar with the machine learning algorithms, for instance, supervised machine learning K-Nearest Neighbors, random forest, ensemble methods, and so on. These algorithms can be implemented using R, or Python libraries. At the entry-level, ML doesn’t require much of math or programming, just interest and motivation.

Apart from these skills, you need to take other skills into consideration like:

  • Analytical Mindset
  • Focus on Problem Solving
  • Domain Knowledge
  • Communication Skills

Now comes the most awaited question:

What types of roles does Data Science offer?

This hot new field promises to revolutionize industries from business to government, health care to academia,” says the New York Times. People have woken up to the fact that without analyzing the massive amounts of data that are at their disposal and extracting valuable insights, there really is no way to successfully sustain in the coming years.

List of Job Roles in Data Science / Big Data

  • MIS Reporting Executive:

MIS reporting executives meet with top clients and co-workers in public relations, finance, operations, and marketing teams in the company to discuss how far the systems are helping the business achieve its goals, discern areas of concern, and troubleshoot system-related problems including security.

  • Business Analyst:

Business analysts (BAs) are responsible for bridging the gap between IT and the business using data analytics to assess processes, determine requirements and deliver data-driven recommendations and reports to executives and stakeholders.

  • Data Analyst:

A Data Analyst is involved in data munging and data visualization. Optimization is a must-know skill for data analyst.

  • Statistician:

They use statistical analysis software tools to analyse extracted data and to identify patterns, relationships or trends answer data-related questions posted by administrators or managers.

  • Data Scientist:

They do predictive analysis of data and along with it, they also use coding to sift through large amounts of unstructured data to derive insights and help design future strategies. Data scientists clean, manage and structure big data from disparate sources.

To know more about how much data scientists make- https://blog.flinkhub.com/everything-about-data-science/

  • Machine Learning Engineer:

They design and implement ML algorithms to address business challenges. ML engineers build data pipelines, benchmark infrastructure, etc.

To know more on Deep Learning- https://blog.flinkhub.com/deep-learning/

  • Data Engineer/Data Architect:

Data engineers collect and store data, do real-time or batch processing, and serve it for analysis to data scientists via an API whereas, Data infrastructure engineers develop, construct, test, and maintain highly scalable data management systems.

  • Big Data Engineer:

It is a highly cross-functional role. Big data engineers develop, maintain a test, and evaluate big data solutions within organizations. Most of the time they are also involved in the design of big data solutions, because of the experience they have with Hadoop[–]based technologies such as MapReduce, Hive, MongoDB or Cassandra”

Companies are running helter-skelter looking for experts to draw meaningful conclusions and make logical predictions from mammoth amounts of data. To meet these requirements, a slew of new job roles have cropped up, each with slightly different roles & responsibilities and skill requirements.

Blurring boundaries aside, these job roles are equally exciting and as much in demand. Whether you are a data hygienist, data explorer, data modelling expert, data scientist, or business solution architect, ramping up your skill portfolio is always the best way forward.

If you want to know what are the industry experts saying about hiring processes and preparations needed for a Data Analyst role, check the video mentioned below.

URL: https://www.facebook.com/flinkhub/videos/1637065403117910/

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