Big Data Internships and Employment: Tips to Find and Make the Most Out of an Internship
Having a high GPA may be something to brag about, but even the best performing students need hands on experience to supplement the knowledge they have learned in the classroom. Many graduates find a steep learning curve when entering the workforce. One of the best ways to reduce this learning curve prior to entering the workforce is to incorporate an internship into your college experience. Read more to learn practical tips to help finding, landing, and maximizing your internship experience.
Why choose an internship in Big Data?
An internship in big data can provide students with valuable computational experience and prepare them for a career in many different fields, whether in big data or related industries such as finance, marketing, banking, and retail.
Leveraging big data is a powerful and relatively new tool that has developed along with rapidly advancing computer processing technologies. Using this data can help provide unique and valuable insights for a variety of applications. The advent of more advanced data collection technologies and improved computer storage has caused the field of big data to grow exponentially. According to Forbes, big data and business analytics will grow from $130.1 billion in 2016 to over $203 billion in 2020.
Interns in big data tend to perform better on job interviews and have a better resume than those applying to data science and business analytics jobs without internship experience, so if you are interested in a career using big data, you should plan to do an internship as a college student.
Are there any disadvantages to an internship in Big Data?
For students seeking to work in big data or a related field, there are no real major disadvantages to such internships. Unlike other types of internships that are often unpaid, many of these internships are paid and can lead to more permanent work in a field that is lucrative and rapidly expanding.
The technical expertise required by the field means that the skills needed for an internship are in short supply compared to traditional internships.
A downside of completing any internship is that, unless it is completed in the summer, the internship can take away from your schoolwork. Luckily, many companies offer summer internships for those interested in data science and business analytics.
Is a Big Data internship right for me?
Anyone interested in big data and its applications should consider applying to internships in the field. Students interested in a career using big data should be good with computers and numbers, and have an interest in technology. Soft skills such as practical thinking, initiative, and communication skills are essential. Data scientists must have strong knowledge in statistics and programming. If you are interested in big data internships but do not have the technical skills, check out the following sections for more information to get up to speed in the field.
What are some skills that I should have to apply to a Big Data Internship?
Big Data internships are tech-intensive and require a background in computer science, machine learning, statistics, artificial intelligence, finance, or related fields. Big data interns should also have good communication skills as the main role of big data professionals is to make a surplus of confusing and varied data make sense, and to be able to relate computational findings to people who may not have a math or science background. In a sense, people who work in the field of big data are data consultants, who are able to interpret a vast library of data and see patterns and trends that can help power decision-making and strategy for businesses and other organizations.
Experience with Machine Learning algorithms, as well as familiarity with concepts relating to Artificial Intelligence and Internet of Things, is a plus. You may also want to take some time to familiarize yourself with Hadoop, which is an open-source software framework used widely in data science for storing data and running applications.
The free website Udacity offers a variety of free multi-week online courses about concepts in data science such as big data, machine learning, artificial intelligence, and other topics. Students can obtain certifications through Udacity which they can list on their resume when applying to big data internships to show demonstrated experience in the field.
Above all, big data analysts (which includes aspiring big data Interns) should understand the environment they are working in and develop smart algorithms to help solve problems and crunch the numbers quickly and efficiently.
Finding an Internship: The Basics
Internship listings can be found all over the Internet – on company and government websites, sites such as Indeed or LinkedIn, or your college’s careers office. To apply to most internships, you will need a resume and cover letter at a minimum. Some internships also require a writing sample or portfolio of previous work, and/or letters of recommendation. If your application passes the initial stage of consideration, you will be asked to interview, so make sure you have a business suit or other professional attire that you can wear to the interview.
10 Tips for Landing an Internship
The following advice is not meant solely for Big Data internships, but for all internships.
- Use active verbs in your resume. Active verbs make your resume stronger and easier to read. A list of action verbs to use in your resume can be found here.
- Double-check your resume for typos. Make sure your resume is clear of spelling and grammar errors. Don’t exaggerate your work responsibilities and list your actual credentials instead of a glamourized version of your work. Employers can easily spot the difference between a good resume with factual qualifications and a resume padded with inaccuracies and even lies.
- Tailor your resume to the internship. If you are applying for a big data internship, make sure to list all of your relevant quantitative and data analytical experience.
- Submit internship applications on time. In most cases, late applications will not be considered. Beat the last-minute rush and start on your application early. Some internship applications require recommendation letters, which should be requested from faculty members and supervisors 3-4 weeks in advance, at a minimum, to ensure that your recommenders have enough time to write you a good letter.
- Prepare for the interview. Use Google to find a list of common interview questions, then record yourself (on your iPhone’s camera or voice notes recorder, for example) answering the questions. You can review the recording as a way to self-critique your responses, speaking style, and body language, and improve them.
- Learn as much as you can about the company before applying. This will ensure that your internship application is as tailored as possible. It will also make your interviews go more smoothly because you will be familiar with the organization’s mission and goals.
- Be flexible. While a big data internship may be primarily focused on learning data analysis techniques, you may also be asked to perform other tasks typically assigned to interns, such as making coffee, picking up food for a meeting, or staffing the office front desk, for example. Be prepared to do some grunt work, as this demonstrates that you are flexible and can help the organization meet its needs.
- Inquire about full-time work. Your goal is to find meaningful employment from the internship experience. Although you may not yet be ready to get a job, ask about whether internships can lead to permanent employment. Although not all big data internships are pipelines to permanent employment in a company, many are, and this can help simplify your job search.
- Be proactive. Nobody is responsible to get you and internship beside yourself. So be persistent (but friendly) in your communications with internship coordinators, and demonstrate that you are a capable, determined, and motivated to obtain the position you seek. This will demonstrate that you are a responsible employee and will work hard.
- Tap into your network. If you are a student in a quantitative field, chances are you know someone who has done an internship or relevant work in big data. If you do not, contact alumni from your school that work at the company at which you are interested in working. Your professors may also be able to recommend contacts. You can use LinkedIn to find people who work at the companies at which you would like to work and use that information to contact them directly through LinkedIn or find their information elsewhere. Consider setting up informational interviews to discuss internship roles and responsibilities with people in your professional network.
5 Tips for Making the Most Out of Your Big Data Internship
- You should seek to work in an internship opportunity that enables you to work on a project from start to finish.
- Make sure to practice manipulating very large datasets using tools such as SAS, SQL, Hadoop, and other tools in your internship to gain experience with data science.
- Present your research to your superiors to gain presentation experience and obtain feedback.
- Work on a project that you can put on your resume.
- Seek mentorship opportunities so that you can stay connected with more established people in the field. This may also help you get hired at the company at which you intern or enable you to obtain a recommendation letter from your intern.
Ways to Get Valuable Big Data Experience in College
- Take free online courses. Use Udacity to take a data science course in topics that range from machine learning and artificial intelligence to software such as Hadoop or MapReduce. Current courses offered include Intro to Data Science, Data Science Interview Prep, Machine Learning, and Big Data Analytics in Healthcare. Students that are serious about a career in Big Data and are willing to spend $499 can obtain a nanodegree in Data Science from Udacity in 7 months (10 hours per week). Students seeking more advanced programming experience in big data can opt for Intro to Hadoop and MapReduce, Real-Time Analytics with Apache Storm (also called the “Hadoop of Real-Time,” used to process real-time data such as Tweets), and Data Wrangling with MongoDB. Coursera also offers a variety of data science courses. Coursera’s Machine Learning course is offered in conjunction with Stanford University and is an excellent resource for those interested in big data.
- Learn how to code. In addition to the courses offered on Udacity, one can learn basics of various programming languages, such as Python, at Code Academy for free.
- Go to data science meetups. A list of Data Science Meetups happening in major cities around the world is listed here. Those who are located in smaller cities may not be able to benefit from such Meetups and may be better off taking online courses to supplement their education and prepare them for Big Data internships.
- Participate in Big Data week. Big Data Week is a yearly conference in Big Data that enables people working in the field to stay updated on trends and discoveries in the field. Even if you do not live near the conference cities (in 2018, they include Bucharest, London, and Chicago), you can watch many of the conference presentations online.
- Take classes in quantitative topics. As a college student, make sure to take courses in topics including math, science, statistics, economics, physics, computer sciences, and machine learning in order to gain the most relevant experience for big data internships and data science in general. These classes will prepare you for a variety of high-paying jobs beyond big data.
- Read up on tech companies. Learn about how companies have used big data to innovate and solve problems. Familiarize yourself with Google, IBM, and other leaders in the field of big data and how they have revolutionized the way companies use data science as a powerful analytical and even decision-making tool. Acquaint yourself with other companies not known for data science, such as Uber, who rely on data analytics to propel their business.
- Sign up for a Kaggle account. Kaggle is a platform used for data science competitions. Sign up and participate in a competition or two to build your programming and data science expertise.
There’s no magic formula to obtaining an internship in data science. Identify your interests in data science and pursue them using the helpful advice used in this article, but remember that big data is a growing and rapidly advancing field and new technologies may emerge in the next few years.
As Roy Rosemarin, Head of Analytics and Data Science at Infectious Media, told the London School of Economics in an interview, “it’s truly hard to give long-standing good advice in such a dynamic technological world, because big data is at the forefront. Just keep up with the world. That’s the best advice I can give to you.”