Are you interested in getting into the data scientist career path? If yes, then you’re on the right page. To become the best data scientist, you need to know what data scientist career paths are there and set the right path for you. If you’re interested in data science, check out our article to find the best data scientist career goals and explore if data science is a good profession for you.
Data Scientist Career Prospects: Why Is Data Science a Good Profession?
Data science is a good profession because of its high salary range and great demand. There’s a huge gap in supply and demand for data scientists. If you possess the right skills, you’ll have tremendous opportunities for advancement in the future.
Also, data science is versatile, so you can work in various fields and industries. For example, you can work in ecommerce, banking, or healthcare. The work and life balance are largely stable. According to a Glassdoor report, data science is the third-best job in 2022.
The job profile of this occupation is largely dependent on the business environment and industry. A data scientist job thrives in technical fields and sectors. They handle complex projects through the use of business intelligence tools.
Data Scientist Salary and Job Outlook
According to the US Bureau of Labor Statistics (BLS), the salary expectation for data scientists is $108,660. When it comes to the job outlook of data science, BLS doesn’t offer data specifically for this occupation. Data scientists are included in the computer and information research scientists category.
BLS data projections show a 22 percent increase for computer and information research scientists until 2030. This means that every year there’ll be 3,200 new jobs for computer and information research scientists. We can say that data science has a prosperous job outlook. There may be varied career path options in the data science field.
What Does a Typical Data Scientist Career Path Look Like?
Stage 1: Junior Data Scientist
Junior data scientists are just beginners in the sector of data science. This is the perfect position for fresh graduates starting in data science. An entry-level data scientist needs to have good technical skills, critical thinking, and programming skills. They’ll work on projects that include analyzing data. According to PayScale, a junior data scientist’s salary is $67,028.
Stage 2: Data Science Manager
It takes at least three years to become a data science manager. This type of profession requires people to have good communication and programming skills. Managers are expected to implement predictive models and model automation initiatives. They also need to have a good understanding of database systems and database management. According to PayScale, data science managers earn around $139,993.
Stage 3: Senior Data Science Manager
A senior manager has in-depth knowledge of neural networks. These skilled professionals use their analytical skills to keep track of code quality and the data science life cycle. It’ll take around five years of experience to become a data scientist manager.
These mid-level data scientists are expected to oversee a team of junior data science members. According to PayScale data, senior data science managers receive $154,090.
Stage 4: Principal Data Scientist
Principal data scientists are directly responsible for data design, development, and management to build new products. This position is considered the most technically skilled because these professionals solve the most complex problems. According to PayScale data, principal data scientists earn around $149,562.
Stage 5: Data Science Director
As a data science director, you should be able to comprehend and troubleshoot complicated system integrations and manage multiple teams. You must also have an extensive understanding of data science, business analytics, and business trends. According to PayScale data, data science directors make close to $158,285.
Data Scientist Career Path: Important Milestones
If you like to become a successful data scientist, it is important to set milestones. To advance your career as a data scientist, you should set milestones to create a data science project or develop relevant data science skills.
- Create your first data science project. Try to make a machine learning model with the help of algorithms. On your first data science project, you can show the practical use of your skills. It’s a good idea to create projects that also involve data wrangling.
- Write your first SQL query and build your first data pipeline. Knowing how to design solid SQL queries and schedule them in workflow management software will make you a desirable data scientist.
- Learn deep learning. Deep learning can handle both labeled and unlabeled data. This kind of learning also produces complex statistical models. Deep learning is extremely useful when dealing with unstructured data due to its capacity to handle vast amounts of information.
- Learn storytelling. If you want to become a successful data scientist, you need to learn storytelling. Data scientists need to have excellent presentation skills. They also need to know how to communicate with stakeholders and explain how their predictive models will create revenue.
- Build a recommendation system. A recommendation system is an algorithm that proposes various products and services to customers based on previous data. Some of the most popular recommendation engines are Amazon and Netflix. Learning how to build a recommendation system is a big plus for any data scientist.
- Learn NLP. Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables machines to read, comprehend, and interpret human languages. NLP allows computers to hear speech, read, analyze, and identify text. Owning this skill is essential for any data research scientist.
Planning Your Data Scientist Career Path
You should make actionable steps to develop a comprehensive data scientist career path. Below are some tips that you can use to help you make a better plan for your data scientist career. These include talking to a data science professional or finding a mentor to guide you in your journey.
Talk to Professionals in the Field
If you feel stuck or don’t know what to do, one of the best ways to get unstuck is to ask someone who has been in the same position. Experienced professionals go through the same process, and they have a deep understanding of the field. If you’re a beginner, talk to an experienced data scientist. They can provide you with advice that can help you.
Find a Mentor
Finding a mentor can help you make informed decisions about your career trajectory. One of the best things you can do to have a successful career is to be mentored by a senior data scientist. Since mentors are more experienced, they have a wide variety of skills available. You can learn how to use those skills from them.
Take a Data Science Bootcamp
Whether you want to get into the data science field or want to advance in it, going on a data science bootcamp is a good choice. You can find different data science programs like Python, SQL, or machine learning. Bootcamps provide hands-on experience and the exact skills you’ll need.
Decide on a Location of Work
If you have the opportunity, it’s good to decide where you want to live. Some states and cities offer better job opportunities and higher salaries than others in this field. Some states and cities can also be more expensive or cheaper than others. According to US News & World Report, a data scientist’s salary is higher in states like California, New York, and Washington.
Research and Learn About Specializations
When you’re starting out in data science, it’s important to look at the specializations of the industry. The knowledge you receive may help you become aware of desires that might otherwise go unnoticed. There’s a wide range of data science specializations that can range from predictive analytics to biomedical informatics.
Popular Data Scientist Career Paths
| Career Path | Skills | Average Salary | Job Outlook |
|---|---|---|---|
| Business Analyst | Business Analysis, Requirements Analysis, Project Management | $70,759 | 14% |
| Chief Data Officer | Data Management, Big Data Analytics, Leadership | $176,693 | N/A |
| Clinical Data Manager | Clinical Data Management, Database Management, and Reporting, Data Management | $75,462 | 33% |
| Financial Analyst | Mathematics, Microsoft Excel, Data Analysis | $62,904 | 6% |
| Systems Analyst | Technical Analysis, System Administration, SQL | $67,700 | 7% |
Next Steps for Aspiring Data Scientists
The next step that you can take as an aspiring data scientist is to attend a coding bootcamp. Attending a bootcamp can provide you with practical skills that can jumpstart your career. Another thing that you can do is to look for data science experts that can act as mentors in your journey.
The data science career path can be a lucrative and fulfilling occupation with the right technical background and mindset. Furthermore, the job entails a bright career trajectory with high demand from various sectors.
Data Scientist Career Path FAQ
First, you must develop high levels of communication skills. Second, be a team player and go the extra mile. Last, seek guidance and feedback from senior professionals.
Yes, a data scientist can become a product manager. Job responsibilities include working with customers and envisioning the product direction. For data scientists to grow into product managers, they need to focus on the activities related to the development of products and services.
Yes, there are other career paths you can choose in data science. Jobs like business intelligence development, product management, and data analytics are occupations that data scientists can pursue.
It’s pretty challenging to become a data scientist, especially with no prior experience.
Data science is a broad field. Knowledge of other domains such as statistics, business, and computer science is required to get a job in data science.
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