How Do I Build A Career In Data Science As An Indian Woman?

You don't need expensive degrees to become a data scientist, and there are many routes to a career in data science as a woman in India.

If you are considering a career in data science, you’ve come to the right place for information.

At Women’s Web, #CareerkiPaathshala is a series where we talk about unconventional or offbeat career options for women. If you have ever thought “I am a woman, I cannot do that job!”, well that is the myth we want to shatter!

Today we explore careers for women in data science. We discuss who is a data scientist, what do you need to learn to become a data scientist, where you might get trained as one, your prospects, pay etc. We help you chalk your own path and build a flourishing career in data science.

But first – a question. Do you know who the world’s most famous and possibly one of the earliest female data scientists was?

I’ll give you a hint: she carried around a lamp with her. Florence Nightingale, that’s who!

I know, she’s the founder of modern nursing, not a data scientist, you are thinking. Well actually, the work she carried out during the Crimean War, were so detailed and backed up by hard data, explanations in simple language and pie-charts – which was still a level method of presenting data back then – that she is, unarguably, one of the best known data scientists!

Welcome to the world of Big Data

The world today is driven by Data. ‘Big Data’, data mining, data modelling, data analytics… the world runs on data. And the avenues for making a career in data science have also widened. In a world run by computers, WE are data. Our every action, decision, even thoughts, are all sorted and stored as data, interpreted by data scientists and analysts, and broken up into chunks, to be used by zillions of companies which sell us everything from tailored holidays to personalised shopping.

And the person that examines this data, analyses it, breaks it down and cracks complex problems is the Data Scientist. The primary job of a data scientist is not to find solutions but to identify potential problems that might nobble a business. The solutions can then be designed.

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Data Science is not one field but an amalgam of many – mathematics and statistics, domain knowledge, programming, communication and soft skills, visualisation and so on. It is a highly specialised field and one that forms the bedrock of many.

Compared to 2019, the data science jobs saw a 62% jump in 2020. (Source: DataQuest) According to the World Economic Forum, by 2022, Data Scientists and Analysts will become the top emerging roles in the world. And by 2026, data science jobs will see a jump to roughly 11.5 million openings.

Where do you look for courses towards a career in data science?

Now we have an inkling of the importance of data science and scientists, let’s start from the top: how can you become one? What training do you need in order to become a data scientist? What are the best data science jobs?

There are many institutions that are offering courses in Data Science. One of the most popular courses is the post graduate program in Data Science and Business Analytics offered by Great Lakes Institute of Management, in collaboration with the McCombs School of Business of the University of Texas at Austin. This course offers Python, SQL, Machine Learning, Data Mining, Predictive modelling etc.

Another top course is the Data Science Prodegree offered by Imarticus, an industry-approved experiential learning program endorsed and collaborated by KPMG. Working on real-world case studies with KPMG provides hands-on experience to the students, making the transition to work mode an easy switch.

Talent Sprint, in association with the Indian Institute of Science, offers an The Advanced Certification Programme in Computational Data Science. Labelled as the ”executive friendly programme”, this 10-month course is aimed at professionals who wish to work with data, develop an in-depth understanding of the mechanics of it and learn to identify insights.

Another top course is the year-long course offered by Simplilearn and Purdue University. This PGP course offers a comprehensive curriculum that is interactive and hands-on.

Another top course is being offered by IIM Calcutta, the Advanced Program in Data Science. Another year-long course, this course is being offered predominantly online, with four days of on campus training. With a completion certificate from the prestigious IIM Calcutta, this course is perfect for those that want to upskill and move up in their career.

With the current pandemic scenario, courses that deliver their content online are ranked high and Coursera, edX and Udemy, as well as Harvard and MIT which have online data science certifications that are highly sought after.

One common thread that runs through most of these courses is they are all of the post-graduate variety. Meaning, you already must have a basic undergraduate degree before attempting these courses. As Data Science is a specialised, interdisciplinary course, it even makes sense to gain a few years of hands on, industry experience before tackling one of these courses and becoming a certified data scientist.

Now that we know where we can get the training, let us answer the all important question: that of cost. How much does a data science course cost? Well, on average, a one-year course costs anything from Rs 2.25 lakhs to 2.85 lakhs.

Some pro tips on how to make a career in data science

Google for top data scientists and you will get a list of men so where are the jobs for women in data science?

As with most fields, data science is a male-dominated field and men vastly outnumber women. But that doesn’t mean that this is field not suited to women. More and more women are breaking into this field and companies like PepsiCo and Google Learning boast of women in the top position, handling their data science divisions.

We spoke to Ritu David, founder and CEO of The Data Duck, Alumbloom and Oasis Health Tech to find out what an average day is like for a data scientist and some pro tips on how to make a career in data science.

(Translated from Hindi)

What are the educational qualifications you need for data science jobs?

What are the job opportunities for a data scientist?

Data science has become such a big word now, and everyone is asking how to enter the field. Right? It takes a lot of hard work and many years of study to become a data scientist, and you start off being a statistician, data analyst, machine learning, engineering which are big fields in themselves.

But this field is a merger of an analytical brain, maths, and computer science. So you can choose to come at it from a mathematical angle, or a computer science angle or an analytical angle. So “data scientist” is not the only job you need to go after. But in the field of data science there are a lot of opportunities.

I mean, today even the way food gets delivered to you through Swiggy or Zomato, requires the work of so many data scientists. Uber, and the way we travel is also all data science.

Everything we do today, and companies you won’t even believe use data science. Like say, Sony Pictures will analyse which picture will be a hit or a flop. That also requires data scientists. Which music will be a hit or not also requires data science.

Earlier our learning was very structured, you could only do certain things if you’d studied science and maths. You couldn’t enter certain fields if you haven’t studied certain subjects. But if you have done an online course of data science, data cleaning, data analytics, then you can get freelance jobs.

Right now there are some courses where you can directly study data science.

But I think, in the indian ecosystem you still need to study IT, software engineering, learn things like Python or study statistics. You don’t have to go at it from a computer science angle, you can do analytics.

What are the specific roles possible in a career in data science?

The data science field is like a stack where you can do basic work like data sorting, data cleaning (to more advanced work). You don’t have to study for ten years, and then work. With the help of online courses you can enter the field in whichever area you want, be it films, medicine etc.

There is a company called Omdena that crowdsources volunteers to take up data science challenges. There was one challenge where they analysed data on domestic violence because it is very underreported and so not tackled effectively. Safecity is an app where you can anonymously document an incident of domestic violence and sexual harrassment.

Omdena took up this data and analysed the parameters that could lead to sexual harrassment and domestic violence such as, what is the community situation that allows for this to happen? What are the situations in the economy that lead this to happen?

So, you can start anywhere and volunteer somewhere, so that you can build your portfolio.

I think that boring way of studying a lot, and doing a lot, that is always there. But if you are of an older age or don’t have the financial means to spend on education, then there are a lot of other ways to get things done, you just have to be flexible and you need to publish a lot online, on your Linkedin page, things like that so people know that you exist. Otherwise how will we find you!

Breaking stereotypes about women in data science

Like many other fields, this too is a field where women don’t have much representation. So what do you have to say about that, and what do you think is scope for women in the field in the future?

There is a data analyst in my team, he doesn’t look like me. He wears a hoodie, has a thick beard, and has messy uncombed hair. And everyone says “yes, he is a data scientist!” What I say is not heard but they listen to him.

I think these are preconceptions of society that if it is a woman, I am not going to look at her unless she “looks like an engineer or a data scientist.” And even women do this not only men, and it is no one’s fault – it is the preconceived notions of people. Look at the heroes of the world right; in software and data science they are all men that look a certain way.

So one is the perceptions about what a data scientist looks like. There is a supermodel Kode with Klossy, she is a supermodel and she codes! But if you see her, people will say things like “her code must not be good” “how can she code” because she is too good looking.

These preconceived ideas come from twenty years ago where we did not have many options. And data science is an engineer’s mindset, very few people go into arts and then end up being a data scientist. I am not saying it is not possible but it is unusual even today.

So I think firstly, we all need to introspect about our biases. What does a data scientist look like to us? Even girls need to figure this out.

The first thing I start doing is that I start underselling the data science aspects, and start overselling my creative aspects because that is what the clients like. And they expect that of me.

Women get a lot of positive affirmations like oh you are very good at speaking, you are very good at communication, presentation, and are empathetic. These may be true but you can still ride a bike! You can still do whatever guys do!

Women need to amplify efforts of other women

I also think it is time for women to help each other in business. We are good at helping each other emotionally. Even for networking, unless we have enough women in data science, it becomes difficult to network and get ahead. In certain industries there are enough women where you can network and move ahead with women uplifting women. But there are still some industries where there is under representation of women, and so it becomes tricky to get ahead.

I just feel that the more of you that join me in data science the better it will be for all of us, because I really believe that today’s woman knows that together we can move forward if we are not in competition with each other. Competition is boring and is for stupid people, collaboration is for the smart. And collaboration is the future and the skill that is most needed in this century.

You don’t need expensive degrees to become a data scientist

With a skill like data science, you can work remotely as part of a team, you can work your own hours. You can work American hours, UK hours, any hours and also be paid phenomenally well. So that financial independence that we need to get as a gender will happen only if we move towards higher paying jobs as a whole.

The more women get financial independence the more other women will get inspired to do the same. And go for those higher paying jobs and don’t hold yourselves back, don’t think I can’t do it and just go for it!

To sum Ritu David up, a data scientist need not have a fancy expensive degree, one can enter the field with online courses as well and build their portfolio and make themselves visible in the industry. It is also an excellent opportunity for women to enter a higher income bracket and gain financial stability and independence. People must change their biases about what a scientist looks like and give women equal opportunity to make their mark in the field.

A data scientist must be innovative, have hands-on experience in data mining, and be able to develop operational models. Having the ability and knowledge to analyse data from a variety of sources is critical. As well as the ability to do research on a vast scale and parse huge quantities of data. If this sounds like you, then Data Science may well be your jam!

Are you a woman at work who’s breaking stereotypes in any of these upcoming/ promising industries – Gaming, data science, AI & ML, cloud computing, digital marketing, social media (influencer) or any other emerging industry that has promising career opportunities.? Come inspire young women.

With #CareerKiPaathshaala, we are creating interesting features and resources on the Women’s Web platform where women can connect, and be featured. We’d like to know more about you! Fill out this form by 10th August.

Image source: LinkedInSalesSolutions on Unsplash

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Lavanya Donthamshetty

Mother, writer, foodie, margarita lover, Lavanya is the exception to the rule that women are multi-taskers. She loves travelling and the top spot on her 'must-visit' list goes to the Irish West Countries. read more...

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