Data Science Career Path: Four must-read tips for launching a career in data science

You’ve got math and science skills, and enjoy data. You’ve had exposure to or maybe even direct experience with programming languages. You’ve heard of machine learning and may even be a pro with deep learning models, but you’re still working in a non-tech related field. Have you considered a data scientist career? Even if you are coming from a diverse professional background or one that doesn’t perfectly fit the mold, the data science career path needs more people with unique experiences and perspectives.

If you are looking to start a data scientist career, gathering expert advice is just as important as learning the technical skills of the trade. Hearing from those who came into the industry before you helps develop an understanding of how professionals from different backgrounds are able to succeed and keeps you connected with industry learnings.

We are proud to introduce you to Python Programmer Giles McMullen-Klein. He started his professional career with a background in financial journalism, working for several years in digital, radio, TV, and newspapers, and medical physics before beginning his data science career path. Learning physics required him to start understanding programming languages in order to look at and analyze results. Programming ultimately created his love for data science and a commitment to teaching others.

Giles has a strong presence on Youtube and interesting insights on Twitter--He regularly shares his data, python and machine learning knowledge on YouTube with over 150k subscribers, which has amassed over 3 million views. Giles began the Python Programmer YouTube channel because starting out he wasn’t a natural with programming tools and now aims to help people learn the programming language that helped things fall into place for him.

He sat down with us and offered us his four expert tips for launching a data science career from anywhere. These tips will help you no matter where you are in your data scientist career path, and are a great resource to pass along to a friend.

1) Stay connected to the Data Science community

Plugging into data science communities will help you discover thought-provoking content you may not know about and industry news that is hot off the press. Connecting on Twitter, listening to podcasts, and checking out educational materials encourages continued learning and ensures you’re wise to industry happenings. Keeping connected on social networking platforms can also create networking opportunities that may serve you well in the future. Networking isn’t just about who you know, what you know is crucial. So, follow away, subscribe, and sign-up for all the newsletters you can--they are free learning resources.

If you prefer to connect in person, look for local data science meetups near you. A google search will likely yield various results for you to choose from and join. Even groups that focus on science, technology, and big data can yield some interesting insights and new friends. Meetups are a fun and easy way to connect with local people who share your interests and can share their knowledge.

2) Keep an eye out for growth opportunities

Starting a data scientist career path also includes finding a company that supports your growth through role availability and mentor relationships, whether you are in the office or a remote employee. Entering a new industry regardless of technical knowledge always means you’re the newbie but use that to your advantage--Ask for advice or help from the seasoned professionals you work with, whether they be data analysts or data scientists. Learning from colleagues will support a position jump in the future, as well as widen your breadth of knowledge.

If you’re wondering what the on-the-job differences between data analysts and data scientists are, ask. Most colleagues have no apprehension talking about their journey and past and present role. Offer to take them out to coffee or lunch. Even a concise genuine email can start a conversation that progresses into a mentorship. If you haven’t had the opportunity to meet people in data science just yet, don’t fret--check our Data Scientist vs. Data Analyst careers breakdown.

3) Find your champions and develop a relationship

Walk the walk, and talk the talk. Developing your data scientist skills doesn’t end after the bootcamp course. Finding an industry champion will help you enhance your data science speak so that networking is easier and real-world learning advances. Talk to other data scientists and see what they say about working in the data science industry and work variances depending on the role. Often times, having a simple conversation with others in your field leads to enthusiastic research and recharged energy during job searching on your part. Ask them to coffee or lunch, or even send a genuine email. Finding like-minded people that you can learn from is indispensable. Learning new topics, including data science is significantly easier with the support of a mentor.  

It’s also a great way to collect interview questions posed in the past for similar roles. This insider tip can be the foundational outline for your upcoming interview preparation, ensuring that you impress any panel you’re in front of. Even if you haven’t found an industry mentor, we can help you begin your interview question preparation--start by reviewing our 10 interview questions every data scientist should know.

4) Highlight your achievements and teach others where you can

A strong portfolio is essential to your success. It shows that you’ve moved from foundational knowledge to advanced skills, can think creatively, and that you’re proud of your work. Portfolios are living documents, websites, or blogs that should be tended to as you complete projects. As you continue to curate your portfolio and present your hard work, your milestones and achievements will start to take on a streamlined narrative. Utilizing a digital portfolio allows you to mention it to anyone you meet, because you never know when you may meet a potential employer, colleague, or mentor.

Blogs can be a supportive resource to your portfolio because they allow you to demonstrate your expertise. Blogs allow you to fully explain your data sources, thought processes, programming language, and your end result. They are also an opportunity to teach someone else. The continued learning model is expanded when you teach others because you are learning the material in a deeper way. Wondering how to transform a project you’re proud of into a blog? Read our Standout student projects blog to learn more and get a feel. Like all preparation, practice makes perfect.

Giles’ final advice:

“Don't give up, don't get impatient. The skills will come, although some days it'll feel like they never will. Learning data science is like learning a spoken language. It takes time to be able to express yourself in a way that you want. Perseverance is key.”

Since data science, in its most basic terms, is the art of using data to uncover insights and make predictions, doing your industry homework and gathering data points from others is really the name of the game. Being as prepared as possible, while learning and interviewing will help you exude confidence to stand sure-footed in your experiences. Navigating on to a data science career path and landing a data scientist career requires persistence, grit, and hard work, without a doubt. However, the rewards of an invigorating high-paying job in tech is worth it.

What Are Data Science Alumni Doing After Thinkful?

Our graduates are earning a median salary of  $75,000 180 days after graduation, and earning over $100k just a year after our program. They are able to continue scaling with state-of-the-art skills and networking techniques they learn from our curriculum. These skills ensure they enter the workforce career-ready and confident enough to connect with others in the field, keep their eye on the prize in the long-term, and continue expanding their portfolios.

They are occupying roles that range from:

• Data Scientist
• Data Analyst
• Business Intelligence Analyst
• Machine Learning Engineer
• Junior Data Analyst

Ready to switch to a data science career? Thinkful offers a full-time five month Immersion course and part-time six month flexible course. Each course is built to help launch a career in data science. Taught by experts in the field, our programs also include consistent one-on-one mentorship to assist you while learning the curriculum and tackling the real-world projects. Following the coursework, you get six months of dedicated career coaching that will get you into your new career. Learning through Thinkful provides reliable support every step of the way.

Apply now for our Data Science Immersion or Data Science Flex program. Learn more. Earn more. Make a change that lasts a lifetime. Because, who doesn’t want to get paid well to do a job they love?

If you are still doing your research and would like to start the conversation with an admissions rep, reach out to us to schedule a call at admissions@thinkful.com. We are here to help you launch your new data science career as it works for you. Now is the time to learn the new skills that can change the trajectory of your life and career.