How does a data science internship increase your job opportunities?
LinkedIn’s Emerging Jobs Report ranked data science as the fastest growing in the world, and is expected to grow to $230.80 billion by 2026.
Data Scientist has remained the most sought-after career choice for over five years and its popularity continues to rise. According to “The Humans of Data Science” report by Michael Page India, a global recruitment company, data science will create around 11.5 million job openings by 2026. The LinkedIn Emerging Jobs Report ranked data science as the fastest growing in the world, and is expected to grow to $230.80 billion by 2026.
Despite the exponential growth of the field of data science, creating millions of new jobs, many data science aspirants, who have acquired good knowledge in data science, find it difficult to get the first job in the field of data science. data science. This is primarily because they lack the practical knowledge to implement data science to deliver business value.
In this article, we will explore various factors influencing job readiness in the field of data science and how the internship plays an important role in this regard.
Data science internship
Internships in Data Science are great opportunities. It is relatively much easier to get a data science internship than a job. Although you won’t earn much from the internship, as a small stipend is paid for your work, you will work on real projects so you can practice your technical skills.
The data science internship offers many potential benefits such as
1. Exposure to real-world use cases: The internship provides a great opportunity to work on real-time projects, interact with customers, and learn from exposure.
2. Flexible hours: Generally, companies don’t expect an internship to take on a full delivery role, so you can use the free time to focus on learning new things alongside your internship work .
3. Practicing technical skills: Internships provide an excellent platform to practice acquired technical skills and understand the difference between real-world data and training data, which is used in the capstone project during the learning phase.
4. Roles and Responsibilities: Understand how data science projects are carried out, the different roles involved and their responsibilities.
5. Stakeholder communication: Data science projects involve multiple teams of business analysts, domain experts, customers/business stakeholders, etc. Effective communication is one of the key aspects and can be acquired through the internship.
6. Network with industry professionals: The internship helps connect with seasoned industry professionals through project contacts and networking. It can be very helpful in your career pursuit.
7. Gain professional experience: Working in real projects as an internship helps to gain professional experience, which adds significant value to your profile in your job search.
8. A job offer: In some cases, the internship can lead directly to a job offer.
How to apply for an internship in Data Science?
A data science internship is the first step towards your career in data science. It’s important to choose the right internship that can help you gain real-world experience and the chance to practice technical skills.
Before applying for the internship, you should cover the following points to ensure that you are ready for the internship.
1. Technical Preparation: A solid conceptual understanding and technical skills required for the internship role are essential. In particular, you should be good at python programming, data preparation, and machine learning modeling.
2. Data Science Projects: You must have at least 20 training/capstone data science projects with machine learning algorithms running end-to-end. It is strongly recommended that you have kept all your code development in cloud repositories such as Github so that you can present it to the potential employer to assess your knowledge on the subject.
3. University degrees, certifications and references: University degrees or certifications related to data science strengthen your profile. Find the correct credentials and pursue them as needed. You can also get references from credible data scientists and professors to help bolster your credentials.
Now it’s time to apply for internships. Below are the few points that improve your chances of landing your favorite data science internship.
• Networking plays an important role in your first internship. Start exploring your relationships through known contacts, through friends and family, and finally through open networking by attending data science related events.
• Share your CV with all potential contacts, show enthusiasm and follow up regularly. Respond promptly to the first invitation to discuss potential internships.
• Explore job sites such as linkedin.com and apply online for potential internships. Also contact the website of your favorite companies to apply.
• When you have multiple offers, evaluate internship opportunities based on learning opportunities and future job prospects.
I hope you find this article useful. Before I wrap up, I like to mention that there is no perfect formula, but the tips above will increase your chances of standing out from the competition in pursuit of your dream career. Always remember that patience and perseverance are essential for professional success.
DataMites is a leading institute for data science courses with nearly a decade of experience training over 50,000 learners. DataMites has industry connections with leading AI and data science companies for internship opportunities. Talk to DataMites advisors for advice.
Disclaimer: No Asian Age journalists were involved in the creation of this content. The group also declines all responsibility for this content.