Data science is an emerging discipline driving research in domains such as statistics, computing science and intelligence science. Its practical applications are deployed in science, engineering, the public sector, business, and the social sciences. Data science includes and draws on artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. It looks for new approaches to data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization. Integrative analytics performed on large sets of data lead to insights that help decision-makers determine the best way forward. (source: International Journal of Data Science and Analytics)
Careers in this field are growing, and demand is high. Remote data science and analytics interns may suffer an embarrassment of riches in terms of choice: most job sites currently have thousands of postings.
Below, we’ll explore what a remote internship in this vertical is like, including what you would be doing and where you could work. We’ll discuss what it takes to do well, how a remote data science and analytics internship can benefit you, and what the application process is like. Finally, we’ll look at actual tasks and requirements included in current postings, and what the future might hold, whether or not you stay on this particular path.
What will I be Doing as a Remote Intern?
Remote data science and analytics interns will be welcomed for their ability to apply their data skills in specified settings. Your knowledge of R, predictive analytics, Unix or Linux, git and other tools, languages and concepts will make you a valuable addition to the team. You could be asked to help find solutions in any aspect of a business or organization. You might design or help out with analytics projects, integrate large and diverse sets of data, or apply data science techniques to solve problems. Applying scientific methodology and algorithms to relevant data will give your employers a better understanding of their work.
You’ll find openings for remote data science and analytics internships in the healthcare industry, with internet-based organizations, in government, and manufacturing. Major retailers, entertainment — especially gaming — and environments from transportation and delivery companies to architects and the scientific domains that gave rise to data science in the first place, can all provide a place for you to work.
Is this Industry Right for Me?
According to Tableau, an analytics platform, good data scientists have a combination of technical and non-technical skills. Non-technical skills that will help you in this industry include critical thinking, effective communication, proactive problem solving, intellectual curiosity, and business sense.
Critical thinking helps open up problems to different approaches. Gathering, questioning and interpreting data in a spirit of objective inquiry will lead to the best possible solutions. Effective communication is necessary to explain what you’re doing to people who don’t have your training. You need to make connections between your efforts and the situation you’re trying to improve, while contributing to your organization’s data literacy. Proactive problem-solving means having an eye for issues that your ability to mine and analyze data will help to address. Your intellectual curiosity provides the drive to find those answers. Finally, a good sense of business is required to grasp the fundamentals of the organization you’re trying to help. You need to know what to look for in terms of the individual business and the broader industry.
Necessary technical skills include the ability to prepare data for effective analysis, leverage self-service analytics platforms, write efficient and maintainable code, apply math and statistics appropriately, and leverage machine learning and artificial intelligence (AI).
To prepare data for effective analysis, you need to know how to source, gather, arrange, process, and model data. Analysis and presentation are also important. Self-service analytics platforms help you share your data with others using easy-to-understand visuals which non-technical co-workers can access through editable dashboards or applications. Your ability to write efficient and maintainable code will help you not only understand the systems you use but also create programs and algorithms to parse data. It’s good to be aware of the many different languages used in data science while focussing on the ones most useful to your situation. Your judicious application of math and statistics will help you identify patterns, design the right kind of test models, and evaluate your data. You can create new analytic tools when needed. The ability to leverage machine learning and AI will help you train and deploy models at the right time and in the best way to help you work more efficiently.
Your remote data science and analytics internship is a chance to test out what kind of environment suits you best. You’ll see what type of employment situation you might prefer (or not) once you put the skills you’ve been learning at school to the test in the real world. Interacting with coworkers in different functions will give you an idea of what’s out there. You could discover new ways to put your skills to work, or new problems you hadn’t considered that you might like to help solve.
How Do I Get One?
Remote data science and analytics interns need basic knowledge in at least one programming language, such as R, Python, or SQL; statistics and probability; and machine learning concepts. These skills are best obtained through formal education. There are many options available. For traditional undergraduate study, U.S. News & World Report has compiled a list of the best programs for 2021. A bachelor’s degree in data science takes around four years to complete. Some schools offer lower in-state tuition. Check out the schools closest to you for options. Also, you don’t have to be a science or computing major to take an introductory course in data science. Berkeley, for example, offers its Data 8: Foundations of Data Science to students from any major, with no prerequisites.
There are also programs available through platforms such as Edx.org, allowing users to access education from top universities. For example, the Elements of Data Science MicroBachelors Program, designed for working adults, is an online course that introduces the underlying algorithms and principles of data science tools. Coursework focusses on the language and theory of linear algebra, followed by signals, systems, and learning, in a 6-month program taught through Rice University. The Professional Certificate in Data Science, offered through Harvard University, is designed to be completed in a year and a half. There are 9 modules: R Basics, Visualization, Probability, Inference and Modeling, Productivity Tools, Wrangling, Linear Regression, Machine Learning, and a final capstone project.
If you already have a STEM degree, you could explore options such as The Data Incubator’s Data Science Fellowship Program. They offer a Data Science Essentials class to help get you started. The University of Texas at Austin offers a 6-month Post Graduate Program in Data Science and Business Analytics through Mygreatlearning.com. Many academic institutions offer continuing education in data science, allowing you to build on your existing experience and education.
Your Resume and Cover Letter
Tableau advises emphasizing a few things in particular to make your resume and cover letter stand out. It’s a good idea to include any “projects that demonstrate leadership, flexibility, and humility.” Bonus points for instances of using your data skills to make decisions. Name the languages you know how to code in, whether Python, Java, C, C#, C++, Ruby, or others. Describe the successes you’ve had with them or project deadlines you met. Customer experience of any kind will look great in your application materials, especially if you can describe some positive impact you had.
On your resume, name the specific technical and coding skills you’ve acquired and briefly describe how you applied them successfully. You can take the opportunity, in your cover letter, to expand on some of the things you like the most about data, or where you feel strongest. Talk about how you would use your data skills to help the organization find solutions. Be sure to address specific issues mentioned in the job posting and how your experience and skills make you the best person for the role. Matching your phrasing to the posting will help get your application through the Applicant Tracking System (ATS).
Your interviews will likely require you to perform a task illustrating your competence. According to industry resource KDnuggets, remote data science and analytics interns are expected to have a solid foundation on which to build your skills, not expert-level knowledge of machine learning or deep learning concepts. To get ready, try projects on Kaggle or practice your Python on Interview Query. Tableau also has free learning materials and one-year licenses for students enrolled at accredited schools. You can take a basic SQL tutorial at Mode. To practice statistics and probability, check out Khan Academy. There are also free classes available from Georgia Institute of Technology. Here are examples of the sort of questions you could be asked, according to KDnuggets:
What is a p-value?
What is regularization, and what problem does it try to solve?
What is the probability of getting a sum of 4 if you have two equally weight dice?
What are some of the steps that you take when wrangling and cleaning a dataset?
What is cross-validation, and why is it necessary?
What’s the difference between an INNER and OUTER JOIN?
For your follow-up video interview, tidy up your space and check your computer equipment, be ready to discuss your assignment, and have questions of your own prepared. Find out as much as you can about the organization and ask thoughtful questions and figure out why you would be a good fit. You can ask friends or look around on the internet for suggestions. Anonymous reviews of remote data scientist internship interviews at a large social media company are posted on Glassdoor. There are reddit threads, with one user answering a question about data analyst internship interviews:
Make sure you have at least one example of a difficult analysis you’ve done. Chances are high that they’ll ask you “explain a difficult analysis that you’ve completed recently.”
Think about things like:
What was the business user’s question/problem?
How did you approach the problem?
What tools did you consider?
Why did you choose the tool you ultimately chose?
What was the solution?
How did you present your findings?
What were your findings?
What impact did it have on the business user?
Remember to dress professionally for your remote internship video interview! Your interviewer will appreciate the effort.
Where Do I Apply?
There are remote data science and analytics internship postings to be found in so many places, you could simply start with an internet search. See if your professors and colleagues have suggestions, if your department has a special affiliation with any organizations, and what your career centre has to offer. Look for postings on CareerUp, and on trusted job sites such as Indeed, Glassdoor and LinkedIn.
The following examples are from actual remote data science and analytics internship postings current as of December 2020.
Data & Analytics Intern (Remote)
Company description: A company providing data-based solutions for the real estate industry.
- Work alongside web developers to implement beneficial changes to the platform
- Daily data review, looking for trends and patterns
- Provide quarterly data and analyses to clients in order to support market updates and insights into general market trends
- Drive the backend of the software platform to build a better database
- Collaborate with engineers, product and customer success teams to identify problems and come up with solutions
- Current student or recent graduate of a bachelor’s program in any subject, with relevant coursework in using analysis and critical thinking to interpret data
- Strong data processing software skill (Microsoft Excel, Tableau)
- Able to work independently, and identify trends to help improve the platform
Data Science Intern (Remote)
Company description: An eCommerce software developer with an international clientele.
- Collaborate on analyses and reports related to computer resource usage (CPU, networking, disk usage, etc.) across a large set of servers and uses
- Perform other analyses as assigned
- Help develop predictive models considering growth, costs and other factors
- Assist management with decision support
- Coursework in statistics, data mining, machine learning and/or programming
- Basic knowledge in statistics and statistical methods such as regression analyses, correlations, Student’s T-tests
- Microsoft Excel
- Any programming language good for parsing data, such as Python, PERL, PHP, etc.
- R and/or SAS
- Awareness of machine learning/classification methods
Data Analytics Intern (Remote)
Company description: An investment management firm with clients and offices all over the world.
- Help to develop data visualization solutions in Tableau
- Assist in training and supporting self-service data tools
- Use Alteryx to support business users’ access to enterprise data sets
- Learn investment management industry key information structures
- Strong analytical skills with experience in SQL or Python and Tableau
- Advanced Microsoft Excel skills
- Great oral and written communication skills
- Resourceful and research oriented, with the ability to find creative solutions to unique problems
What Happens after my Remote Internship?
A remote internship is a great way to launch a career in data science and analytics. According to Glassdoor estimates, data scientists in the Unites States earn an average of $113,000 a year, while data analysts can expect to earn an average of $62,000 annually. Urban centers and bigger companies skew higher in terms of pay. As you progress from entry level to roles of greater responsibility, you’ll continue to learn and add on to your skill set, while potentially having more authority and influence within your organization. Some may opt for master’s or PhD studies as they seek to expand their knowledge and access a greater selection of job opportunities. One day you may find yourself interviewing for the job of your dreams! Or you may discover a particular aspect of data science that interests you and commit your career to making it better.
What Happens if it Isn’t for Me?
A career in data science and analytics is supposed to be one of the most desirable jobs in the world, yet for some it may not turn out to be the best option. You’ll find yourself well-equipped with transferable skills should you decide to leave the field. Web design or other internet-based endeavors may prove more comfortable. You might find your analytical and research skills better suited to less mathematically informed fields such as the social sciences, or even law. Pay attention to the things that made you want to look elsewhere, such as a greater desire to be outdoors or to work with your hands. Talk to people you trust and see what kind of changes you can make while being realistic about the possibility of making less money and having a harder time finding a job. Many people who work in data science and analytics experience frustration and disappointment due to unmet expectations, workplace politics, and other obstacles. As a new profession, there are still many things that have yet to be worked out in terms of making workers feel at home. Employers may have only an obscure understanding of what it is you do, and you may feel isolated at times. Find community wherever possible and trust your instincts.