09 Jul 2022

How To Make A Career Switch To Data Science From Other Fields | Ekeeda

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How To Make A Career Switch To Data Science From Other Fields?

Today’s economy runs more on analytics and performance measurement; thus more and more organizations & businesses have started spending their years collecting huge amounts of data. There is a massive demand for people who can mine and interpret data. These are termed ‘Data Scientists’. LinkedIn’s Emerging Jobs report ranked 'Data Science', as the fastest-growing, most in-demand technology worldwide. Data scientists leverage the power of technology to gain valuable insights from the reams of data businesses. ‘The Humans of Data Science’ says data science will create roughly 11.5 million job openings by 2026. This urge for a great career move, isn’t it? Take a headstart with Ekeeda Data Science Program and upskill with data experts from fortune 500+ companies. Learn Advanced concepts of Data Visualization, ML & Prediction Algorithms, SQL, Tableau, etc. while on the go!

But ever wondered can I switch my career into data science being an IT professional or pharmaceutical company? Yes! You can. Our blog will help you understand the path for a non-data science person to land an exciting job role in the hottest career field – Data Science. Some backgrounds for career switches include – HR, software engineering, Finance, and even a non-technical background for freshers.


Are you looking for a career change to data science? Well! Certainly, you should because it’s one of the hottest job fields in the market. If you’re a student or working professional looking for a career transition to the data science space, then you’ve come to the right place. Fresh graduates can take time to learn and sharpen their in-demand skills. They can take up some online courses to gain knowledge in the subject. Professionals with work experience can also make a smooth transition. Instead of quitting jobs, you can learn data science skills at your comfort time and place, and utilize their skills and competitive advantages gained during your experience in the firm. Today, it feels like suddenly half of the globe wants to move into data science these days, with wonderful perks and a plethora of openings in the industry. Companies are aggressively investing into data science talent to stay or move ahead in the competition or axe out the business competition. As a data science aspirant, it’s the best time to change your career and move to stable growth in life. But it comes with its own challenges. We are often asked in our community on how to switch career in data science. People from all sorts of backgrounds – IT, Sales, HR, Finance, and more – all want to grab a piece of the data science pie.

Let us first put your doubts to rest – it is quite possible to make a career shift to the data science field from your current profession or (studies). And that’s what we will be discussing in our blog ahead; so stay tuned for the next couple of minutes and find out how you do career shift to data science from various fields in the market. Here we will talk about how to make the transition into data science from backgrounds like Software Engineer, Finance, App Developer, Sales, HR, etc., and a few skills required for a data scientist:

If you’re planning a career transition to data science, there has to be the right plan & guidance in place. Ekeeda offers the best data science online program that will help you upskill and become an industry at the comfort of your home or office. With over 50+ modules and 5 capstone projects, it will help you learn data science right from basic to advanced level and step into the industry with confidence. 1:1 mentor sessions will help you clear all your doubts.

Starting a data science career with no proper guidance and planning could be confusing. Relax! We are here to help you. Along with proper guidance, we will help you learn data science from industry experts. Our curriculum meets industry standards and is designed based on the latest trends and technologies. The program is designed with dedicated mentorship and intensive career support for you. After the course completion, you can grab exciting job opportunities in top tech and start-ups like Datascope, Ugam, Peerbits, IBM, Quantum Black, Cabot, etc.

So, let’s begin and see how individuals from other professions are willing to step into the hottest job field of the century – Data Science.

Career Transition To Data Science From Software Engineering

This pick is for software engineers who are looking for a career transition into data science. Here are a few things you should do to get into data science and what kind of roles would be suitable for a software engineer to kickstart their career in this field. To start with, if software engineering fascinates you, then you should consider being a data engineer or ML engineer.  These are not exactly the data scientist roles; however close enough & considered among the larger data science fields.

If you would still like to be a data scientist, you should possess the following skills in your arsenal:

  • Probability & Stats – Not so in-depth at least you need to be familiar with the basics of probability and statistical functions
  • SQL – You will find this word on the internet, in Ads, and nearly everywhere. You might have even used an ORM to interact with different databases. Learn a little bit more about the languages such as window functions, CTEs, triggers, good SQL style guide, etc.
  • Modelling – Learn some good models on how and when to use them. Read the documentation and tutorials online in your comfort. These skills also need domain expertise about things you’re working at – ranging from healthcare to the logistics and finance industry.
  • Data Visualization – To learn Data Analysis is being the most precious thing once you turn it into graphs and diagrams – could be a map, time series, 3D pie chart (just a joke), or anything else 
  • Report – Once you have some valuable insights, you should make them available and organize them into a compelling project. It should be a document or a dashboard that is summarized and easily accessible. 
  • Communication Skills – Finally, once you come up with a dashboard; you should be able to discuss it with ease with your colleagues and superior managers. Although it seems a hard skill to acquire, but its totally worth it in the long run!

You will love to read how a software engineer successfully switched his career to data science and set an amazing career path: How I Became A Data Scientist From Software Developer

Career Transition To Data Science From Finance

Finance is like a natural thing to step into data science, doesn’t it? It’s all about number crunch and the sheer feeling of getting those numbers correct is simply awesome! It blends nicely with the data science world. In fact, the BFSI sector is leading the way in data science techniques and using its utmost potential for indexing and bringing up the best statistics. So, if you come from accounts or finance background, you’re like halfway through your dreams of getting the perfect data science role.

  • If you wanna make a career shift to data science from finance, you will probably need the following things:
  • A degree in mathematics or statistics, computer science, physics, engineering, or subject with major mathematical content.
  • You should be able to program in multiple languages (both compile and interpret) such as C or C++, R, Matlab, Python, and or Java
  • You should possess good database skills in any RDBMS (for instance, My SQL, Oracle, etc.
  • You should be well versed in handling time-series data from Bloomberg, Reuters, or any of the financial data streams.

But there are two important characteristics of individuals who wish to kick start data science jobs in finance:

  • You will need to communicate mathematical ideas both verbally and visually to normal people
  • You should know how to harness their mathematical training to solve genuine problems. 
  • Alongside, you also need a good understanding of optimization, statistical interference, simulation, multivariate analysis, and proper data visualization.

Career Transition To Data Science UX Designer/Research

It’s one of the most interesting career transitions in the world. We never considered UX individuals to be the potential for a career transition in data science.  We would give you a glimpse of learning data science tools while keeping UX experience in mind. Some of the UX design tools are already in use and UX researchers are already routing into using data (qualitative & quantitative) tools and using low-hand data science skills including Google Analytics, JSON, Excel, and user testing data (amongst others).  These are data visualization tools and methods required to do UX and find data patterns. Although, there is a limited scope and reach.

If you want to dig deeper into data science tools and languages, then it gets will get more complex. You will have to learn tools like advanced excel, Tableau, SQL, and programming languages to code with JavaScript with data libraries like D3.js or R. These tools and code syntaxes are hard to learn. We emphasize working with an experienced data science team to learn critical data science topics. As a UX researcher, you should rather work with data scientist than switch to a whole new profession. We think it’s crucial to know what is possible with data and seek out your expertise as needed. Fluency in data science tools with help you work with top data scientists and professionals in the field. Seek help from team members who will help you find new and relevant patterns in your research data.

Career Transition To Data Science From Application Developer

The best way to get into this hottest career field is by first understanding the current technologies. Way back in 2016 there were buzzwords like Data Science, Machine Learning, and Artificial Intelligence. These terms were heard online and we started exploring career options in this field and we came to know that statistics was the base of data science. Thus, it could blend perfectly with the interests of individuals who are fascinated by statistics, data analysis, and number crunching, especially those who are keen practitioners of excel. For them, there is nothing better than working in a field that they would love! 

For most of programmers, you have to stay statistics but those concepts are long forgotten. Making a transition might be tough, but analysis and statistical knowledge will make it happen for you.  During the switch, you will realize you don’t need to forget your possessed skills to learn the new ones. You can make efficient use of your programming skills as a bridge between IT and Data Science to structure your ML code logic.

This transition will also help you understand that the project presentation results vary significantly from process to process, industry to industry, etc. For instance, in the IT industry, the output of a web development project is a web page that is understandable for stakeholders. In data science, the output is numbers and clients might be shell-shocked by the figure. So, as a data science individual, you will have to reveal these numbers to the clients building up an indicative, positive, and interesting story.

For those who wanna Switch careers to data science; we would recommend:  Ask yourself if you're really interested in Data Science Or if you’re just doing it because your friend has chosen it? Are you a good fit or do you just want to add a degree to your portfolio? Don’t just fall for hype and glamour. There are hundreds of resources available online, such as the various articles and blogs on Ekeeda.com to help you build an idea of what you feel about this field.

Check out how an IT individual after working for almost 10 years planned to move into Data Science: My Career Switch To Data Science After A Decade In IT Field

Career Transition To Data Science From Sales & Marketing

Yes! You heard it right; it may seem impossible but it's quite evident that you can make a career transition in data science from marketing and sales. To know how stay tuned ahead! Marketing and Sales experience is really different than any other career. But one thing we need to bring to your attention is – The Sales & Marketing Team relies heavily on data and works closely with analysts. There is no doubt there are many professionals that will be lured by the data science field.  Know more about the skills required to become a data scientist, what your day looks like as a ‘Data Scientist’, and then decide by yourself on it.

We would like to introduce you few realities so that you know what they all assume. We assume you have some experience under your belt in sales: Analytics is not a routine job where people feel I can do it. In fact, it's either yes or not. There is no middle way out. So don’t flatter or get trapped by saying ‘I’ll manage it, sir’. Analytics requires deep knowledge of things like Maths, Statistics, Number Crunch, and programming to a certain extent. Analytics is supposed to help businesses, processes, or rather CEO, VPS take decisions that bring profit and prove to be the game-changer. Thus, it requires a lot of business focus. Trust us, it's not easy as it may sound. People are there for several years and sometimes find it a tussle task to play with numbers. Since you’re new you have to leave your ego and proactively ask questions and show interest, be willing to learn, and unlearn the way things work. Ready for it? Ready to work with freshers who are better at tasks, younger than you? Do you love to play with things like regression, decision trees, cross tabs, graphs & charts, feature engineering, etc. for your entire life then it’s a go-ahead for you.
Behind all the hype and glamor there is intense maths and stats that are sitting and working hard silently. Every presentation and graph has a number of background that speaks for you. 
So be realistic and take a practical decision instead of a glamour call.

Here’s a chance to make a mid-career switch to data science and set a great path ahead! Also, Read: Power Of Digital Marketing To Grow Your Business From Scratch

Career Transition To Data Science From Human Resource

Well, when someone hears about switching to a data science career from HR, it seems to be a distant dream. The first thing would be -  Are you kidding? Is there any connection between these two fields? Certainly, there is and the good news is you can switch your career from HR to Data Science. We will demonstrate how you can make a career transition into data science and make use of the in-demand skills.

Technically, anyone can be a data scientist provided you know programming skills and prove to be the potential employer who can add value to the profile. If you have strong HR experience, it may also logical sense to leverage that domain expertise. For instance, a lot of big companies use Data Science techniques in the HR division for ‘workforce analytics’ to understand employee churn, leave, roster, leadership development, policy implementation, and more. 
You might even do pivot, but it will be hard to start from scratch without either domain knowledge or serious technical chops. But remember salary for data scientist roles might be a little less for someone who will have 8-10 years of corporate experience.

The models used for workforce analytics will translate well to universities, and educational or behavourial health institutes since these are domains requiring ‘people skills and a strong understanding of psychology. For instance, large universities use analytics from LMS (Learning Management System for 1) to intervene students at risk of failing 2) to create personalized student paths, and 3) to update the curriculum to where most of the students struggle.
Ekeeda data science program comes with the guidance of an expert mentor who will customize the learning path, especially for you. Coming from HR background and no clue on where to start? Ekeeda Data Science Program can help you here!

From ‘NO Coding’ Background To Become A Data Scientist

One of the most common questions we see is – will I be able to become a data scientist without a technical or engineering background? YES! It’s possible. Or do I need coding for it? 
You don’t need a Ph.D. or M. Tech or even a hard-core programming background to start learning Data Science. 
There is no background needed to become a pro data scientist in the long run and earn lakhs. It’s all about your interest, and willingness to play with numbers, do analysis and envisage yourself in a role where data and decision-making will be aligned. I would suggest an excellent learning pathway; however, individual learning needs with regard to time & effort will need the right tweaking and help in the path.
Beginners would need to start learning to program if they have no prior experience. You can follow these simple steps:

  • Learn Programming languages like C++, Java, R, or Python and become an expert in any one of the languages.
  • Gain complete insights on subjects like Intermediate Statistics and Probability, Algebra, Linear Algebra, ML Algorithms & Methods, Stats for ML
  • Work with Independent Projects – Try to implement your learning step by step fashion while you solve the objectives of these projects.

On A Concluding Note –

Data Science has helped businesses grow beyond the conventional norms of data consolidation. Data Science is the 21st Century Job Skill that everybody should have. Switching to a data science career could be rewarding and exciting in terms of salary package and perks. However, the path to starting or advancing in a data science career is not so linear. You don’t necessarily need a technical or Master’s degree to become a data science expert. You simply need to new-age skills and experience in order to start a flourishing career in Data Science.

Whether you’re a student or working professional - be it HR or Marketing Manager, Software Engineer or one with ‘NO Coding’ background; anyone can learn data science and accelerate their career growth. Are you looking for a career transition to Data Science from any background? Then you’ve come to the right place.

Check our Data Science Online Program which is designed by industry experts from fortune 500+ companies. Learn Advanced concepts of Data Visualization, ML & Prediction Algorithms, SQL, Tableau, etc. while on the go! It’s the best way to learn data science right at your comfort and leisure time. We offer 1:1 Live Mentorship by experts from Amazon, Google, KPMG, and Microsoft, Cutting-edge Curriculum, 50+ Assignments & 5+ Real-World Projects, 100% Placement Assistance, and Certification from top companies.

Get noticed by 100+ hiring partners: Ugam, Mu Sigma, Cloudera, Brainvire, IBM, Peerbits, and more. Equip yourself with the right data science skills with Ekeeda and secure a 60-80% salary hike in your new job!

Cheers. Good Luck!

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