The LinkedIn’s Emerging Jobs Report ranked data science as the fastest growing globally, projected to grow to $230.80 billion by 2026.
Data Scientist remained the most desired career choice for more than five years and its popularity is steadily increasing. As per the Michael Page India, a global recruitment firm, ‘The Humans of Data Science’ report, data science will create roughly 11.5 million job openings by 2026. LinkedIn’s Emerging Jobs Report ranked data science as the fastest growing globally, projected to grow to $230.80 billion by 2026.
In spite of the exponential growth in the Data Science domain, creating millions of new jobs, many data science aspirants, who have gained good Data Science knowledge, find it challenging to get the first job in the field of data science. This is mostly due to the fact that they lack the practical knowledge in implementing data science to deliver business value.
In this article, we shall explore various factors influencing job readiness in the field of data science and how internship plays an important role in that.
Data Science Internship
Data Science internships are great opportunities. It is relatively much easier to get a data science internship as compared to a job. Though you won’t be earning much through the Internship, as a small stipend is paid for your work, you will get to work with real projects so that you can practice technical skills.
Data science internship offers many potential benefits such as
1. Exposure to real world use cases: Internship offers a great opportunity to work with real-time projects, interacting with clients and learn from the exposure.
2. Flexible Timing: Usually, companies won’t expect an internship to take up a full delivery role, so you can use the spare time to focus on learning new things along with your internship work.
3. Practising technical skills: Internships provides an excellent platform to practise the technical skills learned and understand the difference between real-world data and learning data, which is used in the cap-stone project during the learning phase.
4. Roles and Responsibilities: Understand how data science projects are executed, various roles involved, and their responsibilities.
5. Stakeholder communication: Data science projects involve multiple teams from business analysts, domain experts, customers/business stakeholders etc. Effective communication is one of the key aspects and can be gained through the internship.
6. Network with industry professionals: Internship helps to connect with senior professionals in the industry through project contacts and networking. This can be very useful in your career pursuit.
7. Gain work experience: Working in real projects as an internship helps to gain work experience, which adds significant value to your profile in your job pursuit.
8. A Job offer: In some cases, the internship can lead to a direct job offer.
How to apply for a Data Science internship?
A Data Science internship is the first step towards your data science career. It is important to choose the right internship that can help you to gain real-world experience and opportunity to practice technical skills.
Before applying for the internship, you should cover the following to ensure you are internship-ready.
1. Technical readiness: Strong conceptual understanding and technical skills as required for the internship role is a must. In particular, you should be good in python programming, data preparation, and machine learning modelling.
2. Data Science projects: You should have at atleast 20+ learning /capstone data science projects with machine learning algorithms executed end-to-end. It is highly recommended that you have kept all your code developments at cloud repositories such as Github so that you can present it to the potential employer to evaluate your subject knowledge.
3. Academic Credentials, Certifications and References: Data science related Academic credentials or certifications strengthen your profile. Research the right credentials and pursue them as required. You can also get references from credible data scientists and professors to help you bolster your credentials.
Now, it’s time to apply for internships. Below are the few points that enhance your chance to land in your preferred data science internship.
• Networking plays an important role in your first internship. Start exploring your connections through known contacts, through your friends and family and finally through open networking by attending Data Science related events.
• Share your resume to all the potential contacts, show enthusiasm and regularly follow up. Be prompt in taking up the first invite to discuss potential internships.
• Explore job sites such as linkedin.com and apply for potential internships online. Also reach out to your preferred companies’ website to drop your application.
• When you have multiple offers, do evaluate the internship opportunities from learning opportunities and future job potential perspectives.
I hope you find this article helpful. Before winding up, I like to mention that there is no perfect formula, but the above tips will increase your chances to stand out from the competition in pursuing your dream career. Always remember that patience and perseverance are key to career success.
DataMites is a leading institute for data science courses with nearly a decade of experience training more than 50,000 learners. DataMites has industry tie-ups with leading AI and Data Science companies’ for internship opportunities. Speak to DataMites counsellors for advice.
Disclaimer: No Asian Age journalist was involved in creating this content. The group also takes no responsibility for this content.