Today, when it comes to data science job opportunities, you’re spoilt for choices. It is not just about opportunities or attractive remuneration, but also about the job gratification and the crucial role a Data Scientist plays when it comes to decision making for the organisation.

However, the jobs available are more for aspirants with a considerable experience and background in Data Science job. Hence, as an entry-level aspirant, you need to prepare yourself better to get an edge over others. For beginners, advanced degree in Computer Science, Statistics, Applied Economics and ability to handle large data sets are fundamental requirements for a role in Data Science.

data science job

So, what is the secret to bag the coveted role as a new Data Scientist? Here are some tips:

(1) Sharpen your Coding skills

Data Scientists can handle challenging roles if they have good command over Technical, Mathematical and Analytical aspects of a problem. While the modalities of technical talent is different across companies, expert level knowledge of coding languages like Python/ R, SQL etc. is a must.

Consistent practise and willingness to learn more languages as you progress will also definitely be an advantage when you want to gain new heights in the industry. Along with is, you also need to prepare on practical aspects of Hadoop and Spark.

(2) Learn as much as you can

Even though you have completed a certification in Data Science and feel you are good to go, think again. Data Science is a vast field with new developments happening every day. Stay updated, try to gather new skills and strengthen your basics as much as possible.

The best part about this is, you don’t have to spend a fortune doing this. There are plenty of reliable online resources and informative books & journals for the same. Sign up for one of them and gather as much knowledge as possible. To gain more pragmatic knowledge, and try to network with experts from the field and learn about real-world challenges.

(3) Choose a niche

Data Science job is one of the most talked about today and there are hundreds of candidates competing for the same job. The best way to stand out of the crowd is to choose an area of specialization such as Data Vizualisation, Web scrapping, NLP etc. This shows your keenness in learning various aspects of Data Science job and convinces future employers that your knowledge and specialization will be an asset to the company.

(4) Do your own projects

Data Science job is all about showcasing your skills rather than just talking about your knowledge. The recruiters want to see your expertise and experience in handling data-related projects. However, considering you are a fresh Data Scientist, it is unlikely that you will have a huge body of work to showcase.

But, you can still attempt in your own way. In whichever organisation you are working currently, you can try to do work on the available data set and build models. Initially, you can start with techniques to include data in your day-to-day work and proceed slowly.

This is something you can showcase to your prospective employers as well. Even though this is a miniscule step, it will convince them about your orientation to take organisational decisions based on data.

(5) Create a Portfolio

Once you get used to data you can try to work on independent projects and showcase them on different platforms such as GitHub and Kaggle. The types of project that you need to include in your portfolio are: Data Cleaning Project, Data Storytelling Project, Data Vizualisation Project, Machine Learning Project and a complete project that showcases all the aspects.

(6) Take internship

Just like a research scientist, an employer expects a Data Scientist to be able to build a hypotheses, collate data and run an experiment to validate a hypotheses. If you take an internship in a Data Science lab, research institute or a university, you can showcase your strength in academics and scientific research-oriented field.

(7) Target a small to medium enterprise

Eventually everyone wants to join a big organisation and it is very natural to do so. However, when you start off, you can focus more on joining a small to medium enterprise. This is because which has Senior Data Scientists occupied with lesser but quality projects, who are more available to guide you.

Hence, you are better placed there in terms of learning and development. Also, smaller companies have limited resources to undertake projects, hence they are more open to candidates even with limited practical experience.

Take small steps towards a big future

Finding your first data science job can be a daunting process. You need to connect to the right people at the right time. All you can do is be patient to bag the right kind of offer for you. At the beginning it is not about money or position but about the learning and skill development.

You need to be patient even if you do not get a prestigious role. Even if you are not able to get through an interview, take it constructively and ask for feedback. Not just that you also need to work on the areas provided in the feedback.