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The Ultimate Guide to Build a Career in Data Science

CAREER, a word that can send chills down your spine. We all have different expectations for our careers. Some of us want a chilled out work profile where we go in at a time, do some work, attend a few meetings, log out at a given time. Some of us want to be running the place where we work; some of us want to own our own office etc. Oxford dictionary defines Career as “an occupation undertaken for a significant period of a person's life and with opportunities for progress.” Take a nice look at the latter part of the definition that says "opportunities for progress" thereby suggesting that a career that does not have any opportunities for you to grow is probably not a career.

You need to have a career that can open the doors of success for you. These days Data Science can be that platform for you. A career in Data Science can be very beneficial keeping in mind how most of the companies today are leveraging the power of data insights for their business advantage.

Data Science is an umbrella term that envelops information analytics, data mining, machine learning, and a few other related orders. While a Data Scientist is required to estimate the future in view of the past incidents, Data Scientists extricate important experiences from different data sources irrespective of them being organised or unorganised.

Let us discuss building a career in Data Science

data scientist Who is a Data Scientist- Definition, Roles and Responsibilities

A Data Scientist is a professional who is an expert in gathering, breaking down and deciphering a large amount of information to recognize approaches to enable a business to enhance its activities and gain a focused edge over its competitors.

Primary responsibilities of a Data Scientist include assembling and examining information, and utilizing different sorts of reporting and analytics devices to identify examples, patterns and connections in informational collections. These professionals normally work in groups to dig big data for information that can be utilized to anticipate client conduct and distinguish business risks and opportunities. These experts are entrusted with the job of creating measurable learning models for information investigation and must have experience in utilizing factual instruments, and also the skills to make and evaluate complex predictive models.

A Data Scientist utilizes a lot of information to create a hypothesis, make inductions and focus on the client, business and market patterns. These professionals must have the capacity to convey how to utilize data analytics to drive business choices that may incorporate altering course, enhancing a procedure or item, or making new administrations or items.

What are the critical skills that you need to develop in order to become a successful Data Scientist?

Here is a list of a few things that would help you in becoming a great Data Scientist-

The Ultimate Guide to Build a Career in Data Science infographic

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A couple of colleges offer their understudies with Data Science degrees, which is a prominent choice. This degree will give you the essential aptitudes to process and examine a stunning arrangement of datasets and will help you understand various IT and computer-related analytics techniques and that is just a beginning of a much wider course. A large portion of the Data Science course’s projects will in like manner have a creative and systematic part, empowering you to settle on judgment decisions in perspective of your discoveries. This is the reason you essentially require some introduction at the college level before you straightforwardly adventure into job or training programs.

Data-Driven Problem Solving

You need to have the acumen to recognize a circumstance's salient highlights, by making sense of how to outline an inquiry that will yield the coveted answer, choosing what approximations bode well, and counselling the correct associates at the proper points of the analytic procedure. The majority of that goes along with the knowledge to determine which Data Science techniques to apply to the current issue.

R Programming

A good knowledge of no less than one of the programming language R is for the most part favoured. R is particularly intended for Data Science needs. You can utilize R to take care of any issue you experience in Data Science. In fact, as per the reports, 43 per cent of information researchers are utilizing R to take care of measurable issues. Be that as it may, R has a precarious expectation to absorb and process statistical information.

Python Coding

Python is an incredible programming language for Data Scientists. In light of its flexibility, you can utilize Python for every one of the means engaged with Data Science processes. It can take different arrangements of information and you can without much of a stretch import SQL tables into your code. It enables you to make datasets and you can actually discover any kind of dataset you require on Google.

Hadoop Platform

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In spite of the fact that this isn't generally a prerequisite, it is intensely favoured as a rule. Having a sound knowledge of Hive or Pig is likewise a solid offering point. Familiarity with cloud instruments, for example, Amazon S3 can likewise be useful. An investigation completed by CrowdFlower on 3490 LinkedIn Data Science employments positioned Apache Hadoop as the second most essential expertise for a Data Scientist with 49% rating.

As an information researcher, you may experience a circumstance where the volume of information you have surpasses the memory of your framework or you have to send information to various servers, this is the place where a working knowledge of Hadoop comes into the picture. You can utilize Hadoop to rapidly pass on information to different focuses on a framework. That is not all. You can utilize Hadoop for information investigation, information filtration, data sampling and summarization also.

Apache Spark

Apache Spark is turning into the most famous big data innovation around the world. It is a big data calculation structure simply like Hadoop. The main distinction is that Spark is quicker than Hadoop. This is on the grounds that Hadoop peruses and writes to disk, which makes it slower, however, Spark stores its calculations in memory.

Machine Learning and AI

A good number of data analysts are not capable in machine learning technology and procedures. This incorporates neural systems, fortification learning, antagonistic learning, and so on. In the event that you need to stand out from other Data Scientists, you have to know Machine learning strategies, for example, directed machine learning, decision trees, calculated relapses and so forth. These aptitudes will assist you with solving diverse Data Science issues that depend on the predictions of major organizational results.

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Ability to work with unstructured data

It is important that a Data Scientist should have the capacity to work with unstructured information. Unstructured information is the indistinct substance that does not fit into database tables. Models incorporate recordings, blog entries, client surveys, online life posts, video bolsters, sound and so forth. They are simply some overwhelming writings lumped together. Arranging this sort of information is troublesome on the grounds that they are not streamlined.

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What are the Best Certifications available to get yourself endorsed in the field of Data Science?

Once you have acquired all the skills that a recruiter looks for in the candidate he is thinking about hiring for the position of data analyst, there is one more thing that he looks for and that is certification. You need to acquire accreditation for your skills and only a recognised certification institute would be able to give you that.

Here is a list of a few most famous certifications on Data Science that have been doing the rounds-

  • Apache Hadoop certifications
  • Certified Health Data Analyst
  • Data Science EMC Proven Professional
  • IBM Cognos Business Intelligence certifications
  • Microsoft Certified Solutions Associate
  • Microsoft Certified Solutions Expert
  • Oracle Database 11g Administrator Certified Associate
  • Oracle Database 11g Administrator Certified Professional
  • SAS Certified BI Content Developer
  • SAS Certified Predictive Modeller
  • SAS Certified Statistical Business Analyst


Choosing a field to make a career in can be a great deal. Do not haste that decision. Rome was not built in one day and therefore your career also requires time, patience and constant efforts. We have listed down each and everything that you need to know to take good steps towards building a successful career in Data Science.

A study which was conducted by McKinsey has estimated that by the end of 2018 the job postings for data science will exceed around 4,90,000 jobs but as per the current scenario, there would only be 2,00,000 data scientists who would be available to fill in these positions in the US alone. There is currently a huge demand and supply gap for this field. Hurry up! Pull up your socks and start researching more and see if this can be the career that you want for yourself.

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