Here's Why Data Analytics Is A Great Career Choice For Women

We are fast moving towards a data-driven world. Right from ads that pop-up based on your search history to wanting more personalised data as a consumer in every sector, data is everywhere. And Data Analytics is this very ability to deal intelligently with data.

 

Sarita Digumarti, Founder and COO of Jigsaw Academy, The Online School Of Analytics, has over 18 years of experience in analytics and consulting across diverse domains. She’s helped clients, in India and in the US, to tackle complex business problems by applying analytical techniques.

 

Recently, SHEROES conducted a webinar with Sarita Digumarti on ‘Why Analytics Is A Great Career Option For Women?’ It was an insightful session which saw women equipped with questions, piquing interest in the field itself.

 

But the question is, “What’s the uproar around Analytics?”

 

• Data Analysis Is Everywhere!

Data Analysis is not specific to any particular industry or sector. There are applications of Analytics in marketing, financial services, HR, operations, logistics and much more. At a very fundamental level, there is a huge demand for Data Analysis and the skills relevant to it.

 

• Rated The Top-Most Searched-For Skill

 

Every year, LinkedIn publishes a report of top skills required, based on job postings on LinkedIn. From 2015 to 2017, Statistics and Data Mining were either #1 or #2 in every single country they have a presence in.

 

• Women And Analytics

 

Analytics is a confluence of business understanding, quantitative understanding and strategy building. For this to work, the top skills required are more than just technical. They also involve abilities that women are naturally great at:

 

1. Logical thinking

2. Good communication skills

3. Making sense of your work

4. Being a team player

 

• Not Just About Numbers

 

If you are seriously considering analytics, clearly you have to develop a skill-set. It is a technical skill-set, and not something dealing only with soft skills.

 

Be comfortable with numbers. You can’t be somebody who freaks out just by looking at numbers. The role requires you to deal with numbers, not equations or derivations. There are tools to help you deal with data, once you acquire that skill.

 

Apply logical frameworks to problem-solving. You have to be persistent, along with a high sense of curiosity. Because you are trying to solve fairly complicated business problems, and the answer doesn’t come out in the first shot. Keep asking questions and keep adding that received information to the solution, till you get to the answer.

 

• Technical Skills To Be Prepared For

 

1. A reasonable understanding of statistics and how it applies to business data. We’re talking about applied statistics here.

2. A good understanding of the analytics methodology, which is a framework you apply to solving problems with data.

3. There are 100s of algorithms, but broadly in the analytics industry today, 70-80% work is done on the basis of 3-4 algorithms. You need to make sure that you master those algorithms.

4. A reasonable amount of knowledge of Analytic tools such as Excel, SAS, R, SPSS, Python.

 

• Planning A Transition Through Analytics

 

As An Experienced Employee

Let’s say, you have an experience as an HR professional. When you have 1000s of employees, you have a massive amount of data. To give you an example - predicting the attrition rate, talent management, which colleges to hire from - comes under HR Analytics. And hence, you have to understand the domain.

 

Plan your transition in a way that Analytics becomes an enabler to move to the next role. You can be a person with experience in retail, e-commerce, supply chain, banking etc. If you add Data Analytics as a skill-set to your experience, it’ll help you get roles at senior levels too.

 

“In Data Science and Analytics, domain understanding is very important. An expert in that domain, who can also apply analytics, is always a plus point.”

 

As A Fresher

Jumping in as a fresher is a great idea as well. Data Science and Analytics is not just one career. There are different career options within. It is strongly recommended for freshers to understand which career option under Analytics they want to take up. A career path in Analytics will only help you get ahead with what you have already studied - MBA, engineering, commerce - anything.

 

• Can Analytics Help You Rejoin The Workforce?
  
   

First, you have to be determined that you want to come back to a career. Once you are confident of that, then it is simply a question of getting upgraded on the right set of skills in Analytics, in relation to your past experience/domain. Coming back to work after a break is a disadvantage in itself and for that, you have to work harder than others and put more effort than others.

 

You have to consider the question, “What will make potential employers look at my resume?”

Upgrade to a skill-set of your choice, relevant in current times (after the break). Analytics is an option, especially if you have a business or IT experience, because:
A. Some of that past experience can be leveraged in analytics.

B. Analytics is a very dynamic field and in that sense, a lot of the skills are constantly getting updated.

 

• Here’s Some Encouragement

 

Roopa Kumari reskilled herself with Analytics and using that as an accelerator to push her career ahead, now works as the Associate GM, HR at Origin Learning Solutions.

 

“Jigsaw helped me jumpstart my career. The HR PREDICTIVE ANALYTICS course gave me a lot of insights and beautifully tied into my sense of purpose of being a top HR Professional. Whatever I learned was easy to replicate in my current work environment.”

 

Data Analytics is a good option if you’re planning to re-enter the job market. Consider investing time and money in this course, as a stepping ladder towards your own success. Efforts in any direction never go to vain.

 

To help you better, here’s a list of courses offered by Jigsaw Academy. They also provide candidates with placement help and have tie-ups with world-renowned academic brands, which makes their courses lucrative.