How to get your first job as a Data Scientist

In India, there are more than 1 Lakh data science jobs currently on Linkedin, with an average salary of 10.8 Lakh per annum. That is because, in today’s economy, data is power. The demand for data scientists has cut across sectors. Businesses, governments, and several industries like pharmaceuticals, manufacturing, automobile, and media have become better at delivering results by leveraging the power of data analytics and data science.

With the consistently growing demand, the US Bureau of Labour Statistics predicts there will be 1 crore 50 lakh job openings by 2026. Companies are willing to pay good amounts to talented data science professionals. Experienced data scientists can bag hefty packages, going up to 40 Lakh per year. Hence, data science jobs are sought after by students and professionals alike, who are aware of its thriving job market. 

However, getting your first job as a data scientist will not be easy. That is because data scientists team up with top decision-makers in the organization to form creative business strategies to deal with multiple business problems. Since it is a high-stakes role, companies prefer experienced data scientists who are considered more dependable than freshers. So, it is harder to get your first job in data science, but we all start somewhere! In this article, we share useful tips on how you can get your first data science job. So keep reading.

The Prerequisites

Before beginning your job hunt, you have to make sure you have adequate practical and conceptual skills. Data Scientists are expected to possess a diverse skill set in coding, statistics, data analysis, machine learning, deep learning as well as communication and analytical skills to carry out effective decision-making.

Therefore while searching for jobs, you have to make sure you are all set with the skills needed. There are plenty of free and paid resources out there on programming, data science and machine learning. You can choose the best one and follow through to acquire relevant skills.  This guide assumes you are already working on those skills, so here’s how you can get your first job in data science.

Build an impressive portfolio

While searching for any job, the biggest difference is made by how you present your skills. A project portfolio allows you to effectively showcase your skills to the recruiters. The projects don’t have to be complex, but they must include valuable data models that are unique and future-proof. 

You can build an impressive project portfolio by learning from other skilled data scientists. Kaggle is a platform that provides Jupyter Notebooks environment to compete with skilled data scientists and ML practitioners. It also has a huge repository of the community’s data and code that you can learn from and build impressive models. Other platforms like Driven Data and Data Kind lets you collaborate with other data scientists to solve real-world socio-economic and environmental problems. Being active on these platforms would strengthen your hold over the concepts as you get exposed to real-world issues that data scientists deal with, making you job ready. 

Also, try to present your project on a self-hosted site. Presenting your analysis and results on an interactive interface is as important as creating valuable models to stand out from the sea of other portfolios recruiters get each day. That is why data scientists are suggested to learn web development. 

Create a robust resume

The importance of an impressive resume is undeniable to get jobs in any field. The same is the case with Data Science, where having a resume would make you stand out from the great amounts of data science job applicants. The key is to make a resume that is readable and highlights your top skills and strengths. For this, you can make sure that your resume has consistent formatting and no typos. It should include subtitles, short paragraphs, and bullet points to make it readable. Recruiters now use automated tools to shortlist resumes, so make sure the resume includes relevant keywords and is error-free. 

That being said, the final screening would be done by a human being, so make sure to customize your resume and cover letter for the hiring manager. If you are using a resume template, optimize it to include keywords from the job posting. Employ powerful verbs and numbers to make your resume credible.

Create a Blog

Having a blog complementing your portfolio could greatly help. Because the initial screening is done by the HR team that might not necessarily have a background in data science. Explaining your work through writing makes your data product palatable to people from non-tech backgrounds, building their confidence in your skills. Your blog on a self-hosted website, platforms like Git and Kaggle that also allow you to host your portfolio would help you showcase your strong hold on the concepts employed in the models. 

Networking

Truth be told, many organizations still rely on employee referrals to fill out open positions in their company. Hence, networking becomes extremely important to prop you up in the eyes of a recruiter. With social networking sites, now it’s easier than ever to connect with like-minded people. You can find data scientists and ML specialists on sites like Driven Data and Data Kind or else on Linkedin and establish connections that can bring you exciting opportunities in Data Science. 

Another means to connect with professional and experienced data scientists is through online and offline webinars, conferences, and events. You can search and track these events through Google to meet with Indian data science professionals and enhance your industry knowledge. 

Start with growing startups

While applying for their first job in data science, many freshers make the mistake of applying for well-established or old economy companies. While it is possible to get hired by these companies, it won’t be easy as these organizations have a higher number of applicants and a rigid hiring process. So, going after growing enterprises would increase your chances of being hired. But more importantly, it would provide you with the opportunity for greater autonomy and career growth. 

Take up data-related roles

With the constant development of algorithms and computational power, the field of data science is evolving and expanding as well. Now there are several job titles that have roles and responsibilities similar to that of a data scientist. Data Analyst, Data Engineer, data architect, and business analyst are jobs that also deal with data. Being flexible in your job search and going after such jobs would give you the relevant experience with data to get your first job as a data scientist. 

With experience, the field of data science can open a gateway to job opportunities as an ML specialist and ML engineer as well. So try out for a variety of roles related to data science to set yourself up for success. 

Be knowledgeable in the field and stay up to date

One of the emerging tech skills that are highly in demand, causing a high dearth of people skilled in Data Science and the AI and ML technologies associated with it. Businesses that have understood the power of data are looking for skilled Data Scientists and analysts left and right. 

However, it is a constantly evolving field dealing with technology. This means that you have to constantly keep learning and upskilling. Keeping up with the developments in the field of Data science would alone give you a one-up over other candidates applying for jobs.