How to Level Up Your Data Science Career

In this article, we're breaking down everything you need to know about excelling in a data science career. Dive into the different types of entry, mid and senior-level roles available, day-to-day responsibilities, salary expectations and more!
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There’s no doubt that behind every great organization is an excellent team of data scientists. This role has grown to become absolutely critical to implementing data modeling, engineering solutions and predictive analytics that help guide business decisions at all levels.  As companies have become increasingly comfortable incorporating advanced tools, the demand for data scientists has steadily risen. 

From what type of position and salary you can expect to make at the beginning, middle, and later stages of your career, to the skills and certifications you have to have, we’re breaking down everything you should know about a data scientist career in this article! 

Data Science Skills

Any Data Scientist must possess a variety of skills as a baseline to function in an entry-level position. The position itself is often held by those with a master’s degree and/or several years of experience. Data Scientists are tasked with managing and manipulating large datasets in order to find insights or make predictions. They work with statistical models, algorithms and machine learning technologies on a daily basis to tell a story with data. On the technical side, they are expected to know:

  • Programming Languages like Python, R and SQL 
  • Big Data 
  • Data Modeling and Visualization
  • Advanced Statistical Modeling
  • Principles of Computer Science and Machine Learning

Entry-Level Data Science Roles

Before becoming a data scientist, many professionals take on a less specialized role that still requires the use of foundational data skills. Even though they’re often confused, this might mean starting a career as a Data Analyst. This role is not responsible for using data to find trends, but rather analyzes historical data and runs A/B tests, among other tasks. Another option is to take on an entry-level Python job, such as a Junior Software  or Python Developer. Other roles Data Scientists have had earlier in their career include Database Administrator or Systems Manager, which provides a hands-on opportunity to manage a company’s systems. Finally, sometimes the best approach is the most direct, which might mean getting a foot in the door as a Junior Data Scientist or Data Science Intern

Entry-Level Data Science Salaries

According to data from Indeed.com, entry-level data and development roles like these typically command salaries in the $40,000 all the way up to $80,000+ in some exceptional cases. Proving yourself in this role is an excellent way to ensure long-term career success!

Job TitleAverage U.S. Salary
Data Analyst$65,626
Jr. Software Developer$38,417
Jr. Python Manager$89,208
Database Manager$60,883
Systems Manager$79,971
Data Science Intern$36,475

Mid-Level Data Science Roles

Several years into your career, you might be ready to ascend to the actual role of a Data Scientist. Towards the beginning of their career these professionals work in a more limited scope, given tasks to solve specific business problems. Mid-level Data Scientists transition towards being the ones to seek out and assign tasks, and generally take on more autonomy in project management. The same holds true for those on the software side, who typically transition into senior developer roles. Others might find themselves drawn to the applied mathematics aspect of the job and seek out a Statistician role. Finally, certain budding data professionals might transition into a management or specialist role, such as Director of Analytics, or Business or Operations Analyst

Mid-Level Data Science Salaries

According to Indeed, the average Data Scientist can easily clear a six-figure yearly salary, which makes sense considering the highly specialized nature of the role. Keep in mind that most individuals at this stage of their career have already obtained a master’s degree or worked several years in a managerial position. This figure will once again vary based on geographic location, industry, and years of expertise.

Job TitleAverage U.S. Salary
Data Scientist$114,060
Senior Software Developer$119,355
Director of Analytics$143,478
Business Intelligence Analyst$87,758
Operations Analyst$71,014

Senior-Level Data Science Roles

With the range of 10-20 years into their career, Data Scientists will likely obtain a senior status and take on a larger breadth of responsibilities within their organization. In addition to defining their departments’ scope of work, they must also take a leadership role in mentoring junior team members, architecting the organization’s systems and communicating insights to external stakeholders and C-suite level executives. 

Senior-level employees of this type could also transfer to upper-level engineering roles like Software or Machine Learning Engineer. They could also head their own department, offering the final say on company strategy as Director of Data Science or Chief Data Officer. Finally, some mid-to-late career professionals enter the consulting space. With all the benefits that come with being your own boss and the ability to select projects that match your expertise and interest, there’s no cap on the amount of money you could make in this role! 

Senior-Level Data Science Salaries

By the time one reaches this point in their career, it’s possible to command a salary of at least $150,000. Depending on the company, they might also receive additional compensation in the form of cash bonuses and/or company equity or stock options. Truthfully, the numbers shown here are not a hard limit. Senior data professionals at FAANG (Facebook, Amazon, Apple Netflix and Alphabet, the five best-performing American tech stocks) have reported salaries upwards of one million dollars. So take that as inspiration- the sky’s the limit in the data science field! 

Job TitleAverage U.S. Salary
Senior Data Scientist$138,031
Senior Software Engineer$119,831
Director of Data Science$151,450
Machine Learning Engineer$141,023
Chief Data Officer$282,500
Data Science Consultant$127,397+

Advancing Your Data Science Career

Making the jump from entry to mid to senior level is often easier in theory than in practice. Here are our top tips for putting yourself in the best position to continue climbing that corporate ladder!

  1. Upgrade Your Education – As we’ve implied throughout this article, more than half of all data science professionals have a master’s degree, with a growing number earning their PhD in the field, as well. After finding your footing in the data world with a few years of first-hand experience, you’ll likely want to consider taking steps towards earning these degrees if you truly aspire to reach the upper echelons of the profession
  2. Explore Certifications – A number of top-tier organizations and industry groups offer certifications for data scientists that are widely recognized across the business world. Obtaining a certification indicates your competence and passion for the role to recruiters and is a surefire way to fastrack a promotion. Some programs to start with are the IBM Data Science Professional Certificate, Microsoft Certified: Azure Data Scientist Associate and SAS Certified Big Data Professional. 
  3. Never Stop Networking – You can truly never know where your next professional opportunity will come from. Expanding your network is one of the easiest, but most impactful ways to grow your career. Seek out a mentor in your chosen field who can provide you guidance on the proper steps to take to walk in their shoes. Don’t be afraid to reach out to professionals online or engage in online communities where you’ll find like-minded individuals. Staying up-to-date on the latest data happenings is a great way to demonstrate value to your company.
  4. Stay Up-to-Date – Data Science is one of the fastest-evolving fields, and expected to explode in popularity over the next decade. Demonstrate your passion and become an integral part of your team by keeping up with the latest trends and best practices. Subject areas like artificial intelligence and cloud computing will play an even bigger role in the field than they do already, so be sure to follow along as their use cases grow. 

Learn More About Data Science

This article only scratches the surface of what goes into a professional data science journey! Check out some of the additional resources we’ve compiled about the field on codingbootcamps.io.

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