Career options for data science professionals:4 different roles in the industry

Career options for data science professionals:4 different roles in the industry

Data science has turned out be a buzz word in the industry during recent times. Various companies have recognized the potential of data science to generate actionable insights from structured and unstructured data and thus are demand for data science professionals today.  Not only data science professionals are well paid but, their career seems to promising as well.  Right from the business operations of banks to e-commerce sites are using data sciences in their day to day operations to improve their performance. There are different career paths you can choose as a data scientist.

Data management professional 

It is an IT role similar to the database manager. You need to maintain data and infrastructure which supports it. However, there is no role for data analysis to play here so, there no need for you to learn languages such as Phyton or R. You may need to focus on learning skills like SQL as well as Hadoop-related query languages such as Hive or Pig. You can excel your career by learning key technologies like Apache Hadoop & its ecosystem, Apache Spark & its ecosystem, SQL & relational databases, NoSQL databases.

Data Engineer

This is again one good non- analytic career path in the data science. Data engineer stays responsible to the design and implementation of the data infrastructure which is maintained by a data manager. If the data manager is a car mechanic, data engineer is an automotive designer. Both of them are required by the companies for a proper functioning of the data in the organization. Both data manager and data engineers focus on same concepts to excel in their career. However, their work profile needs them to understand these concepts at different levels.

Business Analyst

As the name refers business analyst role related to analysis and presentation of the data. The role includes reporting dashboards or anything that is related to business intelligence. You may have to interact big data framework as a part of your job responsibility.  The role of the business analyst is primarily about pulling more from the data. The business analyst can be contrasted with two roles namely machine learning researcher/practitioner and the data-oriented professional. Both the job roles stay responsible for eliciting insight from data and require some unique skills to perform the job.

Data-oriented Professional

 This role perfectly defines the reader about what it means to be a data scientist. The data-oriented professional is primarily related to data.  Depending on the role played by the data-oriented professional they have to master different skillset, in fact, this role of the data-oriented professional is a jack of all trades in the data world. The role may include you to work many tasks related to data sciences. You need to have a good domain knowledge to excel in such roles which can be learnt from enrolling the data science courses to kick start your career in the year 2017.

Data Science: Predictive Modelling

Data Science: Predictive Modelling

                What  is  Predictive Model?image2


                                                             Predictive Modelling


Predictive analytics is not only describes what’s happening, they predict what WILL happen in the future.Predictive modelling is the process of creating, testing and validating a model to best predict the probability of an out come.


                                                         Predictive Model Life Cycle


image3 (1)


                                                 Define Business Problem/ opportunity


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                                                Key metrics and data procurement




                                                         Analyze and enrich the data


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                                                          Model building and validation


                                                                  Model Deployment


image8 (1)


                                                                 Monitor and Improve




Sexiest job of the century? Data Analytics

Sexiest job of the century? Data Analytics

Sexiest job of the 21st century is Data Scientist

But What skills you should attire if you are “Aspiring Data Scientist”?

Most of us are now quite familiar with terms like Big Data , Analytics, Data Science and Data Scientist.

But to be a data scientist you should have right mix of knowledge on business, technology and statistical methods.

Technical Skills :

Start Learning R and Python and Jasper, Tableau : R and Python are the two most widely used programming languages used by lot of analytics professionals along with SAS. having these languages in your armory is going to be a huge advantage for you.

Statistical knowledge :

You need expertise in supervised, unsupervised machine learning algorithms.

Example: logistic regression, cluster, factor, decision trees, CHAID, neural networks. Time series and forecasting models.

Business understanding :

Understanding business is key to be a successful data scientist. How do you gain this?

1. Learn From Peers : Lot of professionals in data analytics field are posting their work on their blogs, or sharing the links of their git-hub repositories. You can find many useful posts on blogs like
R-Bloggers , FiveThirtyEight ,Revolutions and websites like Kdnuggets.

Join Data Science Competitions : There are lots of different forums like KaggleCrowdAnalyticx , DrivenData etc. where you can participate in data science competition. You gain lot by applying knowledge on real data sets and also comparing yourself against your peers. There are lot of useful forums and discussion boards on these platforms where you can learn new techniques and approaches.

Develop the Ability of Story Telling : Data Scientist is someone who is not just required to understand the technical and business aspects of the problem, but also needs to explain the end results to top management and CXOs in the form of a story that will enable them to take right business decisions. So start practicing explaining complex business problem and its solution to a person who don’t know anything about it.

Write Blogs , Share Articles : Writing blogs about your work and sharing with it with others is a great way to showcase your work as well as to help others to learn from you. Writing a solution to a complex analytics problem you solved and explaining it in the form of a story can be a great practice to your story telling skills as well.


Aspiring to be a DATA Scientist?

Aspiring to be a DATA Scientist?

To Learn Data Science For Free
This Desk will help you to ASK, ANSWER, SPEAK, LISTEN, READ and GROW

who should learn data science?

– People starving to provide solutions to real time business challenges through Analytics
– People aspiring to be a data scientist
– Interest to know business dynamics
– Love spending time with Data & finding hidden patterns
– Analytics as a career choice
– B-tech grad, Science discipline in Mathematics and Stats, Business Administration (MBA), Pharmacy discipline
– People having a job or study related to finance
– People having a job or study related to Marketing
– People who are very analytical and want to see how this field is related to them
– Students who want to explore this career option

Why you should learn data science?

– Data scientist “the sexiest job of the 21st century”
– Not just data scientist. These mechanisms can be used in varied fields like BFSI, Health Care, Travel and Tourism, Retail & CPG, marketing and many more
– Huge career growth opportunity for free
– Learning is not difficult if you have Analytical mind set

How you should learn data science?

Our experts in the field will help you out with how to get going about it

  • You will get to hear from domain experts
  • Tech geeks will help how BIG you need to aim technically
  • Statisticians share advanced modelling experiences
  • You will get to hear on innovations in the data science industry
  • You will get to know market trends and insights

What you should learn in data science?

  • Three WH’s you should be asking your self
  • What subjective knowledge I need to learn?
  • Who will get me domain knowledge?
  • Which technical knowledge gives me advantage?

What careers you can think after learning data science?

– Statistician
– Social Media Analyst
– Business Analyst
– Digital Marketing Analyst
– Data Engineer
– Machine Learning Expert
– Mathematician
– Financial Analyst
– Data Scientist

“Sharing is caring”

In an attempt to through light on those unsolved, untold, unseen, unknown sides of the Analytics world.

This is an attempt to bring together the wide voluminous knowledge spread across length and breadth among this group to the focal spot of every individual.

To enlighten everyone on all those “WHYs”, “WHATs”, “HOWs” of the analytical process that has been put to some cold storage of the brain by each one of us.

Well the journey has begun with a lot of motivation but it’s the habit that will keep us moving.
The habit to explore, learn and share one’s learning with others

Have a ASK (Attitude to Seek Knowledge) and keep watching this space for more on data science