Entry Level Data Science Jobs

• Blockchain Council
• January 07, 2025

Data science has become a sought-after career path, with companies relying on data to guide their decisions. For those looking to join this fast-growing field, understanding what entry-level roles involve and knowing what kind of salaries to expect can be helpful. 

Common Entry-Level Roles in Data Science

For beginners, starting in data science means taking on entry-level positions. These roles generally require familiarity with basic data handling, statistical methods, and programming skills. Some of the most common entry-level data science jobs include:

• Data Analyst: A data analyst’s primary task is to gather and process data. This involves cleaning datasets, analyzing them, and presenting findings that help businesses make smarter choices.
• Junior Data Scientist: Those in junior data scientist roles work closely with senior professionals to develop models, run experiments, and solve specific business problems.
• Business Intelligence (BI) Analyst: BI analysts focus on analyzing company data and presenting insights to management teams. Their job involves reporting on key performance indicators (KPIs) and helping businesses improve their decision-making processes.
• Entry-Level Machine Learning Engineer: Beginners in machine learning engineering assist in developing basic models and algorithms. They often work under supervision while learning how to implement solutions in real-world settings.

Entry-Level Data Science Jobs Salary Expectations

The salaries for entry-level data science jobs depend on various factors, including region, industry, and individual qualifications. Here’s a look at what beginners can typically expect to earn in different parts of the world:

United States

The average annual pay for new data scientists is around $78,482, with most salaries ranging from $69,687 to $85,041. Those working in high-demand areas like San Francisco, Silicon Valley, or Seattle can earn significantly more—up to 28% higher than the national average—due to intense competition in tech hubs.

India

In India, especially in cities like Kolkata, the average entry-level salary for data scientists stands at roughly ₹931,000 per year. Salaries can vary based on city and employer, with major tech cities offering better pay.

Other Regions

In Europe, entry-level data science professionals in tech-driven countries like Germany or the UK can expect starting salaries ranging from €40,000 to €55,000 annually. Meanwhile, countries in Southeast Asia are seeing increasing demand for data scientists, though salaries may be lower compared to North America or Europe.

Factors Affecting Entry-Level Salaries

Several factors play a role in determining how much an entry-level data scientist can earn. Here’s a breakdown of key elements:

Educational Background

While a bachelor’s degree in a relevant field (such as computer science or statistics) is usually sufficient to secure an entry-level role, those holding a master’s degree or higher may have access to better-paying opportunities right away.

Technical Skill Set

Proficiency in widely-used programming languages like Python, R, and SQL can lead to better compensation. Employers also look for experience with data visualization tools and familiarity with basic machine learning concepts.

Industry

Certain industries, such as finance, technology, and healthcare, offer higher salaries. This is because these sectors heavily depend on accurate data interpretation to guide crucial operations.

Geographic Location

Salaries are often higher in metropolitan areas and tech hubs. However, cost of living in such locations may also be considerably higher, so it’s important to weigh this factor when considering job offers.

Company Type and Size

Larger organizations or those in highly competitive industries tend to offer more generous compensation packages. Startups, while often paying less initially, may provide more growth opportunities in the long run.

Important Skills for Beginners

If you’re aiming for a role in data science, focusing on the right skills can boost your chances of landing a well-paying job. Key areas to work on include:

• Programming Languages: Knowing how to code in Python, R, or SQL is crucial. These languages are used in nearly all data science tasks, from data cleaning to model building.
• Statistical Methods: A sound understanding of probability, regression analysis, and statistical modeling helps in interpreting results correctly.
• Data Visualization Tools: The ability to present your findings clearly using tools like Tableau, Power BI, or even simple libraries like Matplotlib in Python can help you stand out.
• Machine Learning Basics: While deep expertise in machine learning isn’t required for beginners, knowing how common algorithms work (such as linear regression, decision trees, and clustering) is beneficial.
• Communication Abilities: Since data scientists often work alongside non-technical departments, being able to explain technical findings in simple terms is a skill that can set you apart.

Boost Your Credentials with a Certification

Gaining a recognized certification in data science can increase your chances of getting hired and help you negotiate a higher starting salary. One program worth considering is the Certified Data Science Developer® offered by the Global Tech Council. This certification covers essential skills, including data handling, visualization, and machine learning basics. Completing such a program not only enhances your knowledge but also shows potential employers that you’ve invested time and effort into building expertise in this field.

Certifications can act as proof of your abilities, especially if you lack significant job experience. They demonstrate that you’re ready to take on real-world challenges and can handle the demands of entry-level data science jobs effectively.

Trends in the Job Market for Data Science in 2025

As of 2025, the demand for data science roles continues growing. Job openings in this sector are predicted to increase by 36% by 2031, making it a top career choice in tech.

Still, hiring in the tech industry has slowed down. Companies are adopting a more cautious approach, prioritizing key roles in artificial intelligence while cutting back on entry-level hiring. This trend has made it harder for beginners to land jobs, resulting in tougher competition.

Wrapping Up

Data science remains a promising career choice for those interested in working with data to drive business decisions. Entry-level data science jobs offer competitive salaries that vary based on location, industry, and personal qualifications. By focusing on building essential skills, pursuing certifications, and staying up-to-date with industry trends, you can improve your chances of securing a great role and earning a respectable income right from the start.

Whether you’re fresh out of college or switching to data science from another field, having a clear plan for skill development and career progression will help you succeed. With dedication, continuous learning, and the right opportunities, a fulfilling career in data science awaits.