Top 5 Entry-level Job Roles in Data Science
Top 5 Entry-level Job Roles in Data Science
By 2026, the U.S. Bureau of Labor Statistics predicts that there will be a further 27.9 percent rise in demand for data science skills.
There are currently 194,000+ Data Science jobs in the United States which clearly indicates the massive demand for data science professionals. If you are wondering whether you should pursue a career in data science, now is the right time! Here are the top five entry-level roles you can pursue in the data science industry.
1. Junior Data Scientist
Junior data scientists gather, organize, validate, clean up, and structure large amounts of raw data for further processing by senior data scientists. At this level, budding data scientists are introduced to the majority of data job functions while honing their coding abilities and understanding of applied mathematics. The annual average salary of junior data scientists in the USA is $95,000.
2. Junior Database Administrator
A junior database administrator helps in managing a database-driven website or application but is only assigned a limited number of administrative duties. They will assist with a database's regular function as a junior database administrator. They build new databases and tables, track efficiency, and troubleshoot when their databases experience issues. The average junior database administrator's salary in the USA is $65,000 per year.
3. Junior Business Analyst
In contrast to most data science positions, a business analyst will most likely be a member of the accounts team. Business analysts at the entry-level collaborate with more experienced analysts when planning, allocating resources and assessing business models. They collaborate actively with various departments to analyze current market and business data. They must recognize issues, observe market trends, assess industry standards, and discover business insights. They must be experts in data modeling and visualization software like advanced Excel. The average junior business analyst's salary in the USA is $60,000 per year.
4. Junior Machine Learning Analyst
A junior machine learning analyst will manage machine learning operations, perform statistical analysis, and handle artificial intelligence (AI) systems. Most of their focus will be directed toward the various supervised and unstructured machine learning techniques, such as k-means clustering and linear regression. The majority of a machine learning analyst's time is spent ensuring that predictive models built using a wide range of data are accurate. The average salary of a junior machine learning analyst in the US is $103,522 annually.
5. Junior Data Analyst
A junior data analyst organizes and analyzes data, and they typically collaborate with senior analysts and analytics managers to learn how to apply a variety of tools. They also help other associates with tasks like cleaning up data and organizing projects into priority lists so they can be finished quickly. The average junior data analyst salary in the USA is $57,223 per year.
Pro Tips To Land Entry-level Data Science Roles
Here are a few useful tips to keep in mind if you want to land any entry-level job role in the data science industry-
- Build the Right Skills
You need to be familiar with key concepts in mathematics, statistics, and probability. You also need to know Python, R, or SQL, have experience with one or more data visualization tools, and possess additional soft skills like business knowledge, communication, and presentation skills.
- Practice Real-World Projects
Once you have mastered the foundational data science skills, it’s time to explore and get your hands on real-world data science projects to apply those skills and knowledge. Build a portfolio of all the projects you have worked on to showcase your expertise to the recruiters. You can try open-source projects from Github or Kaggle.
- Earn Data Science Certifications
Certifications are an excellent way to get one step ahead in the competition when the demand for data science professionals is rapidly growing over time. Gain any professional data science certification by platforms such as IBM, Google, Microsoft, Coursera, etc.
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