Careers rarely develop the way we plan them. Our career path often takes many twists and turns, with particular events, choices and people influencing our direction.

We asked Elva Bannon from Smart Futures to give some advice for people considering this job:

Elva Bannon

Mechatronic Engineer

Smart Futures

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Elva Bannon

I found having education in a number of different areas of engineering to be beneficial to the work I am doing.

There is a whole world of possibilities out there for engineers, and it is difficult to know what subjects are necessary for the industry you will end up in. I was always interested in robotics and environmental issues, but it was not until my Masters that I really knew what I wanted to do.

General entry courses are quite useful, as you get a taste for a few different areas before you have to specialise, a lot of companies offer on the job training, and there is also the possibility of further study.

An engineering qualification teaches you so much more than just the technical subjects, but a way of looking at the world and solving problems in a logical and systematic way.

Engineers are sought after for these skills as much as the technical ones, and it opens up incredible opportunities. Engineering is not an easy route through college, but it is incredibly rewarding.

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The Social person's interests focus on some aspect of those people in their environment. In all cases the social person enjoys the personal contact of other people in preference to the impersonal dealings with things, data and ideas found in other groups.

Many will seek out positions where there is direct contact with the public in some advisory role, whether a receptionist or a counsellor. Social people are motivated by an interest in different types of people, and like diversity in their work environments. Many are drawn towards careers in the caring professions and social welfare area, whilst others prefer teaching and other 'informing' roles.
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What a Data Analyst does

What is Analytics? What does a Data Analyst do?

A large number of students / young professionals ask me this. Especially when they see the articles from Mckinsey stating Analytics is the next big thing in business and that there is a substantial shortage of manpower. 

Or when Harvard Business School takes out an article saying,”Data Scientist: The Sexiest Job of the 21st Century” 

Analytics is simply the use of numbers to decide on business problems / situations. Thus, in a world where there are huge ERP systems, Internet information, Mobile apps etc. there is a large volume of data that is created and stored by an organisation . The old way of work was – if you need to make a decision, call the person who has experience in that area and take his advice. Was it the best way? Perhaps not, because human beings develop biases basis the atmosphere / situations / education they have been subject to. Also, it has been found that though a human being can effectively judge the effect of one factor on an outcome, he /she finds it difficult when the number of factors are many and the data is huge. Better decisions are made with the use of statistical techniques which allow us to work on the data and come to a conclusion.

The next question often is – So what is the type of ‘use of numbers’ that we are talking about? Will I have to sit and do maths again?

The last decade has seen the advent of SaaS (Software as a service) in all walks of Information gathering and manipulation . Thus, Analytics systems now are button driven systems which do the calculations and throw up the results . An Analyst or Data Scientist has to look at these results and conclude / make recommendations for the business to implement.

For example, an ICICI bank wants to sell loans in the market. It has data of all customers who have taken loans from it over the last 20 years . The portfolio is of, say, 1 crore loans. It now wants to understand which customers should it give a pre-approved loan offer.

The simplest answer may be – all the customers who paid up on time every time in the earlier loans. Let us call this set of customers Segment A . But on analysis you may find that customers who defaulted but paid up after default actually made more money for the bank because they paid Interest + Late payment charges. Let us call this set Segment B . Hence, you can now say that you want to send out the offer to Customer A + B. However, within Segment B there was a set of customers who you had to send Collections teams to their house to collect the money. So they paid Interest + Late payment charges- Collection cost . This set is Segment C. So you may then decide to target Customers A+B –C.

You could do this exercise using Decision Tree software which cut your data into segments for you.

The last question that we will tackle in this article is – What does the work day of an Analytics professional look like ?

A typical work day may look like the following :

  • He will walk into the office and be told about the problem that the business needs his inputs on
  • He will determine which is the best way to solve the problem
  • He will then gather the relevant data from the large datasets stored in the server
  • Next, he will import the data into the analytics system
  • He will run the technique thru the software (SAS, SPSS, XLSTAT etc.)
  • The software will produce the relevant output
  • He will study the output and prepare a report with his recommendations
  • This will be discussed with the business

The companies which recruit large teams in Analytics include TCS, Accenture (Mumbai), McKinsey Knowledge Centre (Gurgaon) , Genpact (Bangalore and Gurgaon) , Novartis (Hyderabad) , Dell (Bangalore), Capital One (Bangalore ), Capgemini (Mumbai) etc. It is expected that there will be a shortage of Analytics resources in the world (and India) in the next decade.


Article by: Subhashini - IBS Blog