2027 Entry-Level Jobs With a Data Science Degree

Imed Bouchrika, PhD

by Imed Bouchrika, PhD

Co-Founder and Chief Data Scientist

What entry-level jobs can you get with a data science degree?

Approximately 60% of graduates in quantitative fields begin their careers in roles that emphasize data analysis and business intelligence, reflecting robust entry-level hiring trends in the United States. These initial positions provide essential experience in interpreting data and supporting organizational decisions.

Below are common entry-level positions for graduates with a data science degree and how they help build foundational skills.

  • Data Analyst: This role involves collecting, cleaning, and analyzing datasets to uncover trends and generate reports. Entry-level data analysts develop expertise in SQL and visualization tools, which lays the groundwork for more advanced analytical responsibilities over time.
  • Business Intelligence Analyst: BI analysts convert raw data into actionable insights through dashboards and metric tracking. They learn to optimize data queries and communicate findings effectively, enhancing their ability to influence strategic planning across teams.
  • Data Engineer: Entry-level data engineers construct and maintain pipelines that ensure smooth data flow and storage. This position deepens programming skills and knowledge of cloud infrastructure, supporting career growth into specialized data architecture roles.
  • Machine Learning Engineer Intern or Junior ML Engineer: These positions emphasize developing and deploying machine learning models. Beginners engage in data preprocessing and feature engineering, gaining hands-on experience with algorithms and languages like Python or R, which are critical for advanced ML roles.

Those interested in accelerating their career development may also consider 4 week certificate programs online, which can provide focused training on practical skills relevant to these entry-level jobs in the data science field.

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Which industries hire the most data science graduates?

Data Science graduates are sought after across diverse sectors due to their analytical expertise and ability to turn data into actionable insights. Approximately 40% of these graduates find employment within technology and finance, reflecting where demand is most concentrated. The wide-ranging applications of data science skills lead employers from various industries to offer entry-level roles.

Here are some of the leading sectors hiring data science degree holders.

  • Technology: As the largest employer, the technology industry leverages data to optimize products, enhance user experiences, and drive innovation. Common entry points include roles like data analyst, business intelligence analyst, and machine learning engineer.
  • Finance: With heavy reliance on data for risk assessment, fraud detection, and trading, the finance sector hires data scientists as quantitative analysts, credit risk analysts, and financial modelers within banks, insurance firms, and investment companies.
  • Healthcare: Increasing use of data science in patient care, medical research, and operational improvements creates opportunities for healthcare data analysts and clinical data coordinators who convert complex data into practical insights.
  • Retail: Retail employers utilize data science to enhance customer experience, optimize supply chains, and personalize marketing, recruiting roles such as consumer insights and inventory analysts for entry-level professionals.
  • Government: Public agencies use data scientists to aid policy development, public safety, and resource management, often providing entry-level positions in data management and program evaluation.

When asked about his experience navigating these industries, a Data Science degree graduate described the job search as a "mix of excitement and uncertainty." He recalled struggling to pinpoint which sector aligned best with his skills, noting that "each industry valued different strengths and had distinct expectations."

He emphasized the importance of persistence and adaptability, explaining how initial interviews helped him better understand where he fit professionally. This firsthand account highlights the varied landscape of opportunities and the personal challenge of finding the right industry fit after graduation.

Which entry-level data science jobs pay the highest salaries?

Salaries for entry-level roles in data science can differ significantly based on specific job functions and the expertise required. Positions such as data engineers and machine learning engineers typically command higher starting wages due to their technical demands.

Below is an overview of some of the top-paying entry roles.

  • Data Engineer: These professionals develop and maintain systems that enable efficient data collection and storage. Their technical skills in programming and database management help them earn starting salaries usually between $75,000 and $95,000, placing them among the better-compensated newcomers.
  • Machine Learning Engineer: Focused on crafting algorithms and predictive models, this role blends software development with advanced statistical methods. Entry-level pay generally ranges from $80,000 to $100,000, reflecting the specialized expertise needed.
  • Quantitative Analyst: Applying mathematical models for risk evaluation and financial forecasting, these analysts often receive salaries from $70,000 to $90,000. Their work's direct effect on business outcomes contributes to their relatively strong compensation.
  • Data Analyst: Concentrating on interpreting existing datasets and producing reports, data analysts start with salaries roughly between $60,000 and $80,000. While their earnings tend to be lower, proficiency in analytical and visualization tools remains essential.

The variation in pay highlights the value placed on technical complexity and impact within different roles, helping graduates align their career choices with both skills and salary expectations.

What Graduates Say About Entry-Level Jobs With a Data Science Degree

  • Yeshua: "Starting my career in data science has been an exciting journey, especially because I was open to remote entry-level roles that offered flexibility without compromising learning opportunities. When choosing a job, I prioritized companies with strong mentorship programs and clear paths for growth, which proved crucial for my professional development. These initial roles have not only built my technical skills but also boosted my confidence to tackle complex projects early on."
  • Hugh: "Reflecting on my first year after graduating in data science, I realized how important it is to align an entry-level position with your long-term career goals rather than just salary or location. I carefully considered the company culture and its commitment to innovation, which greatly influenced my choice between hybrid and onsite roles. This mindset has helped me secure a role that feels meaningful and sets a solid foundation for future advancement."
  • Atlas: "Landing an onsite entry-level role in data science was challenging but incredibly rewarding, especially because it allowed me to build stronger in-person relationships and network effectively. I focused on finding roles where I could work on real-world datasets and cross-functional teams, which gave me practical experience beyond theoretical knowledge. These early experiences have become key assets in my ongoing career progression and have made me more adaptable to varied work environments."

Other Things You Should Know About Data Science Degrees

What are typical tasks for entry-level data scientists in 2027?

In 2027, entry-level data scientists typically handle data cleaning and preprocessing, build and test simple machine-learning models, and contribute to data visualization and report generation. They also assist in data collection efforts, ensuring data quality and consistency, utilizing tools like Python, R, and SQL.

What are average salaries for entry-level data science jobs in 2027?

In 2027, entry-level data science positions typically offer salaries ranging from $65,000 to $85,000 annually, depending on the company size, industry, and location. Data scientists in tech hubs like San Francisco or New York City may start with higher salaries due to increased living costs and market demand.

What programming languages are essential for data science entry-level jobs in 2027?

Essential programming languages for 2027 entry-level data science jobs include Python and R due to their widespread use in data analysis and machine learning. Additionally, proficiency in SQL is crucial for database management tasks in many data science roles.

Are entry-level data science jobs usually project-based or ongoing work?

Entry-level data science positions can involve both project-based and ongoing work. Some roles focus on short-term projects that provide analysis for particular business questions, while others contribute to continuous data monitoring and model maintenance. The balance depends on the company size and industry but starting with defined projects is common for beginners.