Is a Data Science Internship Necessary for Getting a Data Scientist Job?
About 25 out of the 30 people roaming around you have either already pursued or are pursuing a data science course. But how many of them got (or will get) a successful data science career?
Yes, it's a big question as of now. Although the data science field comes with endless opportunities, still, a career transition into the same might be a bit tough.
From that aspect, internships are a great help in introducing data science newbies to the industrial picture. Data science internships increase your chances of networking with others in the field. Not only that, it helps you get hands-on experience, participate in team discussions, work with advanced data sets, and set an understanding of the impact of your work.
We live in a jet-fast and extensively competitive world, where theoretical knowledge goes to the back row while the experience of its practical application comes into the limelight.
Recruiters don't have the time to consider or analyze the fact that you are a fresher and might lack practical experience. But still, you can prove yourself fairly in the field.
Yes, it's a hard truth, and you have to prepare yourself if you get adopted in such a realistic world.
The world of data science is currently holding a stack of amazing opportunities. There are plenty of data science certifications and master's programs available. But at the end of the day, you need to showcase your practical experience to get your first data science job. So, a data science internship is keenly necessary for getting a data science job.
Data science is a much more organized discipline to take part in. All you need to have is smartness and consistency in your efforts.
What does a data science intern do?
The shortest answer will be assisting junior data scientists. As a data science intern, you need to assist data scientists in extracting, cleaning, analyzing, and interpreting data. The critical role is to help data scientists gain the most valuable insights and make the most profitable data-driven decision.
Although the exact roles vary from internship to internship, the brief remains the same as follows:
Assisting in data collection, handling, and cleaning
Supporting data analysis
Becoming a helping hand in predictive modeling
Communicating the result through the right and targeted channels
And last but not least is participating in projects
What are the benefits of Data Science Intern Jobs?
Completing an internship provides proof of your technical abilities. Recruiters can refer to the skills you have learned and your position in a data science project.
Through a data science internship, one can gain real-world experience. Practicing the technical and soft skills required and enhancing them further will make you a better candidate for MNC-based data science jobs.
Your experience level also helps you understand your position and how well you can handle the work in a company setting. You can evaluate if you will be able to manage the workload.
Internships also lead candidates to connect with a network of industry professionals through whom they can get jobs, referrals, etc.
What should be the objective of a data science intern?
Instead of traditional learning goals like achieving certificates, focus on gaining deep knowledge of the basics. Strengthening the base data science theories will help you to cope with any kind of business problem.
There are no one-size fit solutions in the data science field. Every problem needs varied solutions. So while learning, your target should be earning more practical experience on the variable problem where you will hone your skills to imply theoretical expertise in real-world scenarios.
Try to involve more in the core task instead of light testing or review tasks throughout your internship phase.
Try to work on unique and 'from scratch' type projects. Instead of having a light work internship, search for a working pressure-loaded data science internship. Your goal should be to join a small team of interns where you can take on the possible number of responsibilities on your own.
What to expect in a data science intern job?
As a data science intern, you will be asked to
Have expert knowledge in at least 2-3 languages and of the tools frequently used in the field.
Be confident with absolute knowledge of those concepts that you choose at the beginning.
Get into other concepts slowly and steadily.
With ongoing time as an intern, you might feel extensive mental stress because no matter how many different languages you learn, the insecurity of other people being more talented would no doubt haunt you.
But one should relax as the whole process happens within a team. The only thing to keep in mind is to focus on the quality of your participation. And the most significant point to be noted is having clear and shining communication with your reporting manager and teammates in what you have done.
Let's have a better idea.
Every Data Scientist is put in a team; this way, each individual's skills in a programming language of their choice are used.
If we interpret the individual work of different teams in a Venn diagram, there will be an intersection and overlapping of various languages among one another.
This means the team may know some required languages but will always be aware of what they do not know.
Therefore, every team has a specific necessity in a project.
As a data science intern, your focus must be on following the patterns of how the activity works and analyzing which language will be appropriate to learn. Your data science learning does not end when you get a full-time job, but rather it starts from there.
What is the ideal educational background to become a Data Scientist?
Well, the answer to this question is a bit tricky. The mostly communicated answer is like below:
A bachelor's degree in a related field where you want to learn is the minimum requirement for pursuing data science. This includes basic knowledge of computer science, maths, and statistics.
So, can't a non-cs background candidate become a data scientist?
Yes, they can. In fact, anyone with knowledge of advanced mathematics (12th standard to college level) is more than enough to step into the world of data science learning. The programming expertise that anyone can learn if they own the passion.
There are specific concepts that must be learned and practiced in data science intern jobs. Also, since it is a dynamic field, the requirements and essentials will change regularly, so it is necessary to be well-groomed before stepping into the field.
How to start preparing for an internship in data science?
People with different domains or educational backgrounds must find a training platform to ease them into the field by providing full knowledge of the concepts right from the beginning.
Getting into the field is easy, but you must pace up your game to sustain.
So always choose a data science course that offers the latest industry-demanding training along with real-time projects and placement support.
However, always put the extra effort from your side instead of betting 100% dependent on your training institutes. Register your profile with your capstone project portfolio on sites like Internshala, LinkedIn, Kaggle, SimplyHired, etc.
Knowing how to handle the toughness and updating yourself according to the data science trends can surely allow you to cope with data science intern programs.
What project should I work on to get a data science internship?
Work on projects that enhance the necessary skills required in the industry. Trending projects in the field will showcase your abilities as a data scientist to prospective employers. It will increase your chances of getting an internship. New and updated projects will show the recruiters that you understand the field and are ready to be an intern.
Here are some trending projects topics to focus on:
Sentiment analysis
Recommendation system
Customer segmentation
Always remain updated about the best data science projects that are in demand across startups and MNCs.
What are the best companies to do a data science internship for?
Look for internship opportunities in companies that apply data science in the prevalent sectors.
As you search for companies, look for the ones providing experience in trending applications. As a data scientist, you should have enough experience by the time you finish your internship to start a career successfully. So look for valuable internships.
Here are some top companies for data science internships:
IBM
Microsoft
Pinterest
Meta University for Analytics
Netflix
These companies all require data science interns with the least qualifications.
Does Google have internships in data science?
Yes, Google offers summer internships of 10-12 weeks. Usually, the application process starts in October and closes in February. You can either apply through Google's dedicated career page or by submitting your well-crafted PDF resume to the Google HR mail IDs.
But keep in mind that three will help me with lakhs of resumes. So, prepare your portfolio smartly. Even after that, you have to pass the interview process. For that, you need hard preparation.
Related blog:
Ace The Toughest Data Science Interview With These Stunning Tricks
Which startups are hiring interns for data science in India?
While MNC internships offer the best ever skill recognition, it's usually harder to get. However, as you grow in your data science career, your in-hand efficacy is going to be the biggest asset. From that aspect, internships in promising startups offer the best-ever opportunities. Here you work in a small team that makes the chances of gaining the best possible in-hand project experience than MNCs.
Below are a few such startups offering internships for data scientists.
Captain Fresh- Bengaluru
NuvoRetail- Remote
UniAcco- Greater Kolkata
Assurant- Mumbai
Eaton- Pune
Tips to grab data science intern in a top MNC
You want to be the best when applying for internships. Therefore, you must consider the following tips to help yourself.
It would be best if you were prepared, so when applying for a position, start looking in advance to ensure ample time to prepare for that particular company.
Applying to as many data science intern jobs as you think are suitable is a better way to start, as you'll put yourself ahead of the competition.
Getting a recommendation letter at the starting point will ease the pressure at the final moment you join as a data science intern.
A portfolio of your previous and current works will help your case for the data scientist internship. Similarly, you will be required to submit your resume and cover letter; therefore, be prepared nicely.
A network of professionals will be a great source of information in approaching your preferred big data internship position and the application process.
Instead of applying only through job searching and internship listing sites, have a constant eye on the company's dedicated career websites.
Search for company-specific data science interview questions in Naurki, Linkedin, and Glassdoor.
Well, groom yourself regarding communication skills and public speaking.
Pro Tips: You should consider programs that provide domain-specific training in data science, as it will help you upscale your career quickly.
How to get into the broader field of data science post-internship?
Ultimately, it comes down to your preparation for a stable and fast-growing data scientist position. Getting into the data science industry is difficult, but you may achieve it through hard work and proper guidance. Data science internships may be the one place where you get to start your career with the right push. Therefore, you must be aptly prepared to apply for such a position.
You should not keep the expectation that you will certainly be chosen as one of the permanent data scientists in the same company once your internship is over. Better to keep applying for a permanent job and attend the interview when 60% of your internship is complete. Although few MNCs offer permanent roles followed by internships but those opportunities are for outstanding performers.
So offer your best during the internship, and try to stick to your expertise domain or industry. This will ease your career path as a successful data scientist.
Concluding tips:
Sharpen yourself in critical research. Be curious about 'why something is not happening?' and 'why something is easily happening?' Never skip even a single possibility unnoticed.
Always try to be a good storyteller who helps you to convince others with your analytical perspectives.
And last but not least, achieve a strong business acumen, which will help you to find out the most profitable analytical solutions.
Best of luck.
