Data science is an ever-evolving industry with highly applied products across many fields. Yet, where should you start if you are a fresher in this career?
There are many jobs that fresh graduates or newcomers to data science can choose to pursue their careers. The entry-level data science jobs I recommend below will be suitable for many people, special newcomers.
1. Data Science Intern
Finding an internship is something you should try whether you’re in college or just graduated. A data science internship is an excellent chance to put what you’ve learned into practice and hone new skills.
You’ll work with data-savvy professionals as an intern. This job requires you to collect and classify data using different methods.
Some companies will allow interns to contribute to their projects to develop new machine learning models, software, or techniques. Interns can even learn how to make connections between data already in the system quickly.
You must equip yourself with specific computer skills and background knowledge to participate as an intern. Some small businesses require interns to be proficient in Excel or primary programming languages like Python, C++, or R.
2. Data Engineer
College graduates can choose to start as full-time data engineers at corporations or in demand. Of course, you will need to know about data types, collection, storage, and analysis methods.
After spending time honing the right skills and experience, you will get an offer with a high salary and many other benefits.
Compared to other candidates, engineers with a strong background in math and machine learning will be the ones who can grow faster.
Besides, you will have a perfect career path if you are proficient in SQL or Python, which is vital to building large projects.
3. Data Scientist
Many excellent students have chosen to become data scientists because of their high incomes. Specifically, $85,000 to over $100,000 per year is the salary they can earn, which is superior to other professions.
Collecting, analyzing, and reporting results on project metrics is a task that a data scientist must complete daily. They often have to work with complex data sets and machine learning models.
You have to master using Python and SQL for your job. Some companies even ask you to analyze data related to business and economic changes.
4. Database Administrator
Managing websites or apps and user information is a task that data administrators need to handle every day. Knowledge to perform data processing and analysis through Python or SQL is required.
In addition, mastering data analysis tools like Toad or SQL Management Studio will also become a strong point for employers to pay attention to your CV.
5. Machine Learning Analyst
Machine learning data analysts are the ones who get high salaries every year for their work. A machine learning analyst can earn up to over $100,000 per year.
But you must handle difficult and complex tasks to receive this great reward. You must use your knowledge to improve various machine learning, including unsupervised and supervised machine learning.
After mastering the simple tasks, you must go deeper into deep learning and neural networks. Linear regressions and k-means clustering are the skills you need to work with these complex structures.
This job will require a strong computer science and math background. Besides, data skills are crucial for you to apply for a machine learning analyst position.
6. Basic Data Analyst
Knowing the data processing processes, you can work as a primary data analyst in large companies. Accordingly, you can apply your data skills to big projects and learn from other experts.
Your earnings will increase with work experience. Yet, you have to master programming languages in data analytics science.
For its downside, you may face tight deadline pressures and a lack of sleep to keep up with projects. Hard work and patience will be vital to work long hours.
Entry-level data science jobs are not easy to handle. So, you will need excellent technical and soft skills to get good results.
You need basic technical skills in computing and technology to become a data analyst or database engineer. What you need is more than just data processing tools. You have to have good logical thinking when dealing with problems.
For example, probability theories will help you get things done better. Meanwhile, classification and regression are knowledge that people working in machine learning need to master.
Proficiency in Python and SQL programming languages is a great advantage, which can help you quickly get an excellent job with a high salary. Plus, you will easily impress HRs if you are good at working with large data sets.
Besides having professional knowledge, you must train yourself with communication skills, time management, and a sense of responsibility at work.
The ability to organize and manage your time well will help you complete your heavy workload and still have time to rest and relax.
You must meet regularly and report your results to colleagues in other departments. So, soft skills are essential to make it easier for you to work.
The difficulty of getting a data science job depends on your education, experience, skills, and current job market.
A bachelor’s degree in a related field, such as computer science, statistics, or math, can help land an entry-level job in data science.
- Online Job Boards: Online job boards like Indeed, Glassdoor, and LinkedIn are great resources for finding entry-level data science jobs.
- Company Websites: Many companies post their job openings on their own websites.
- Networking: Attend industry conferences, meetups, and events to meet other professionals in the field.
Are you ready to start your data science career with one of the entry-level jobs we listed above? The options I introduce above are all jobs that bring high income and a great career path. If you are passionate about computer science with many solid skills, quickly submit your CV for these positions.
Good luck with your chosen path!