How to Find a Data Science Job Abroad: A Step-by-Step Guide
How cool would it be to land that dream data science job abroad, to live someplace new, exciting, exotic?
If you ever thought about doing just that, but didn’t know where or how to begin, settle in for a quick read and we’ll show you how to make that dream a reality, step by step.
Trends in Data Science
Before we jump into the how-tos, let’s take a look at some trends in the data science field.
Yet, despite being the sexiest job of the 21st century, many positions are still unfilled across the globe. Why? There is a shortage of talent. The last several years have seen a rapid surge in demand for data science jobs abroad. And IBM estimates that by 2020, demand for Data Scientists and Analysts will leap by 28 percent.
Sectors that are trending as emerging markets are in financial services, manufacturing, and logistics. And with General Data Protection Regulation (GDPR) becoming ever-more important worldwide, jobs in the government sector are expected to boom, as well.
Advantages of Data Science Jobs Abroad
Aside from the idea of working seaside or in a romantic ancient city, surrounded by culture and excitement, working abroad has many benefits you may not have considered:
- Income: Globally, data science careers are some of the most profitable. Across the board, salaries worldwide are lower than in the U.S., but this should not deter you. The cost of living abroad is typically less expensive, too. Therefore, lower salaries can be quite competitive in comparison. You might be surprised by the lifestyle you can afford with a fraction of the income.
- Cultural experience: This may be obvious, but we’ll repeat it here. Living immersed in another culture, surrounded by new customs, people, and languages can be an enlightening experience. It can add a perspective, and even intrigue to a mundane routine.
- Environment: Relocating for a dream job abroad allows you to choose how you live, from the community to the climate. A change of scenery can be an excellent boost to moral as long as the climate and location suit you.
Are You Prepared to Work Abroad?
The next step is to prepare yourself as the best candidate. Data science is a blend of a number of disciplines in math, statistics, and science. But its implementation is also specific to industries. Specializing in a specific sector will narrow your search and the competition. You’re more likely to be considered for a position if you have experience in sector for which you apply.
Every data scientist should have strong skill in the following:
- Programming tools
- Data visualization and communication, intuition, and wrangling
- Machine learning
Other valuable skills that will help you land that dream job are:
- Multivariable calculus and linear algebra
- Software engineering
Specifically, you will need to demonstrate skills in data coding. According to an article posted in Medium.com, you should have experience in:
- bash/command line
ICO.com reports that Foote Partners believes that advance data analytics will be the driving force behind IoT (Internet of Things). The must-have skill set in IoT is:
- Apache Hadoop and related modules (HDFS, HBase, Flume, Oozie, Hive, Pig, YARN)
- NoSQL and NewSQL
- Apache Spark
- Machine learning and data mining
If you possess the skills listed here, you’re in good shape. If you are a little rusty or insecure about your abilities, you might want to consider polishing up on them before plunging into the job hunt.
Most companies are looking for a candidate with a solid academic background combined with on-the-job experience. Cio.com, a tech news resource, provides a list of “26 Big Data and Data Analytics Certifications” featuring courses from major players from Amazon Web Services (AWS) to Stanford Data Mining and Applications graduate certificates. The courses can be expensive, but they’re worth the investment to bolster your career and appeal. Alternatively, online courses are more affordable, but may not offer the certificates.
Depending on the company’s needs, some skills are more important than others. Above all, as a data scientist, you will need to be versatile and adaptable.
Once you have identified the job that most appeals to you, understand the expertise needed to work in that field and focus on optimizing the desired skill set for that sector. Now that you have selected your coveted role and you are prepared to excel, you are ready to move forward.
How to Find a Data Science Job Abroad
How do you find data science jobs abroad? The easiest way to locate data science jobs abroad is to use a combination of online job search engines, job boards, networking and Google.
The key to locating overseas jobs is to use search engines that are specific to the country. Include the country name in your Google search for job boards and you should get a selection of boards focused on the region.
When researching where to find jobs in data science abroad, work smarter, not harder. Jobbatical can help you locate available positions in countries around the globe in tech, business, and creative industries. Applications for positions vary and new positions scattered across Southeast Asia and Eastern Europe arrive weekly. Utilize filters to target specific regions or pay a small fee to access targeted results.
Aside from internet dating, job boards are probably the oldest internet profession. As such, there’s always a new kid on the block. Here are a few boards worthy your attention:
A final option is networking. This can provide valuable information regarding market possibilities and job opportunities abroad.
- Sites like Kaggle and Stack Overflow host an online worldwide community that caters to knowledge sharing and career building and are a good way to network with another data scientists worldwide.
- Showcase your work on sites like Github and Jupyther Notebook for international exposure and employment opportunities.
- A summer internship with a prospective employer can also open doors to overseas employment.
Recruiting agencies can also be helpful; however, be sure to review any contract obligations first, as they may require a percentage of your income as compensation.
Submit Your Application
Your resume is the company’s first impression of you. Make it a good one–one that will last. Before you submit your resume, be prepared for the interview. You don’t want to scramble to get a portfolio ready when a call comes in to set up your first interview.
- Carefully review the job description, and adapt your resume to show your expertise in each skill the position requires.
- Tailor your resume and cover letter to the company and the job requirements. Don’t let your resume get lost in the sea of generic communications. The idea is to stand out as exceptional.
- Address your application to a person whenever possible. Knowing the name of the hiring contact will make a big impression.
- Make sure your contact information is available and correct. Again, this may seem obvious, but the mistake is more common than you may think.
In addition, when applying for jobs overseas, be sure to pay attention to spelling. Make sure your resume matches the local language; for example U.S. English vs. U.K. English. There’s a notable difference.
Remember, there is an extra burden on companies to hire foreign workers. Convince them that the increased effort is worth it by being flawless in your presentation.
Applying for Multiple Jobs at Once
To score a Data Science job abroad, you’ll not want to put all your eggs in one basket. Applying to multiple jobs at once will give you a far greater chance of scoring your dream job. However, when applying for multiple jobs at one time, there are a few things to be aware of. Here are some pointers:
- Apply for one job at a time. Don’t risk getting job details confused by doing the same step (ie. writing your cover letter) for many jobs at one time. Look at each job application on its own, and complete it from start to finish, before moving on to the next one.
- Write a fresh cover letter for each job. Don’t copy/ paste from your last one. It will look forced, and your potential employer will know something is up. Writing your cover letter from scratch will allow you to really personalise it towards the role in question — something potential employers require.
- Organize and rank your job applications according to the ones that stand out most for you as idyllic. Put more time and energy into the ones that seem perfect for you, and follow up, follow up, follow up.
Nailing the Interview
The primary advice for interviewing is the same for just about any job. By following the basics you’ll have a good start. However, In order to really shine as a data scientist, you’ll need to prepare to interview at differering technical levels depending on who is conducting the interview.
- Do your homework. Formulate and rehearse answers to the most common interview questions so you appear relaxed and articulate. Inc., an online news magazine offers a list of 27 most Common Interview Questions and Answers that can help you prepare.
- When recruiting internationally, companies will rely on phone interviews, Skype, or other video conferencing tools. You should make sure all equipment is working in advance and eliminate any possible interruptions such as your phone.
- Try to schedule a time that is convenient for the interviewer. Remember, they are likely in a different time zone, so show them initiative and flexibility by scheduling a time that’s convenient for them.
- Have questions for the interviewer: Just about every interviewer will ask if you have any questions. This is the time to impress them with your knowledge of their company. Put together a question or two that shows that you know who they are, what they do, their current projects, and even about their company culture.
- Dress the part: When doing an “in-person” or video conference interview look professional. Even if the interviewer cannot see your whole person, it is recommended that you dress for the occasion. It will make you look and feel more confident.
- Save questions about the relocation and transition until after an offer is made. You want to be enthusiastic, but humble as well.
- And as always, it is a nice touch to send an email afterward, thanking the company for the opportunity.
When interviewing a for a data science position:
Depending on the size of the company, you may have an initial interview with someone from, say, human resources for vetting purposes, and with any luck, a second or even a third interview to follow.
- Know who your interviewer is and adapt: If you have an initial meeting scheduled with HR, this is not the time to pull out the technical jargon and try to sell the importance of data analytics. Let’s face it, many people do not understand what you do as a data scientist.
- In a subsequent interviews, you will likely be talking with someone who is more savvy to the position requirements. Again, since not everyone understands your job description, consider who the interviewer is before trying to dazzle anyone with your brilliance.
- If you are interviewing with the data science department head, then you will need to impress them with your working knowledge. You’ll want to be able to answer questions about programming, algorithms, machine learning, and the tools you use. If you have scheduled enough time, have a presentation or a portfolio prepare to share. Your portfolio should have examples of your work, reports, and even content (blogs, guest articles, etc.) to demonstrate your programming and communication capabilities.
- If you are interviewing for the top spot in the data science division, you may, again, be interviewing with someone who still may not fully understand the details of how you perform your job. Even the best CEOs may not know the details of how data analytics work. In this case, be prepared to sell your trade and its importance (the benefits) to the company.
- Most importantly, be prepared to answer questions about how you handle different people in a variety of situations. They want to know how you solve problems. You need to demonstrate your ability to effectively communicate your findings–and their relevance–to the company directors.
- Finally, be patient. Stories on the internet abound about data specialists applying at over 100 companies before landing that dream job in data science.
Accepting the Offer
Congratulations! You nailed the interview and the job is yours if you want it. Don’t panic. Now comes the most important part of the data science abroad job hunt.
- Read the job description and make sure you have a written contract that you understand. Consider having it reviewed with legal assistance before signing on for employment if you are unsure of anything.
- Be clear about what is expected of you and the position.
- Review the employment laws of the country.
- Review work permit requirements and visa regulations for the country you are moving to.
- Know the type of visa, time frame of the visa process and the visa application requirements both for you and the employer.
- Know your net salary and the cost of living to determine if you can afford to live reasonably well abroad.
- Talk to your accountant to determine if you are still obligated for taxes in your home country.
- Ask about moving expenses or if accommodation is provided as part of the contract.
- Finally, determine with your employer what your start date will be.
This has been quite an achievement for you. You made the decision to pursue a data science job abroad you upgraded your skills and gained expertise in certain areas. You applied for the job, nailed the interview and got the job offer. You made the arrangements and you’re set to embark on your data science job abroad.
You’ve worked for this adventure, so enjoy it. Take in the sights, soak up the new experiences, and explore your new environment. Now, update your bucket list!