Salary for Entry-level / Junior Data Scientist during 2024

Salary details

The average entry-level / junior Data Scientist salary lies between USD 69,722 and USD 142,000 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Salary trend

Top 20 Job Tags for Entry-level / Junior Data Scientist roles

The three most common job tag items assiciated with entry-level / junior Data Scientist job listings are Python, Machine Learning and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Python | 1235 jobs Machine Learning | 1023 jobs SQL | 840 jobs Statistics | 806 jobs Engineering | 684 jobs Computer Science | 668 jobs R | 647 jobs Mathematics | 508 jobs Research | 447 jobs Data analysis | 387 jobs Big Data | 280 jobs ML models | 265 jobs Testing | 245 jobs Azure | 241 jobs NLP | 231 jobs AWS | 224 jobs Data visualization | 223 jobs Deep Learning | 221 jobs TensorFlow | 211 jobs Power BI | 204 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Data Scientist roles

The three most common job benefits and perks assiciated with entry-level / junior Data Scientist job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 863 jobs Health care | 369 jobs Flex hours | 297 jobs Team events | 225 jobs Equity / stock options | 207 jobs Startup environment | 178 jobs Competitive pay | 178 jobs Medical leave | 176 jobs Insurance | 172 jobs Salary bonus | 170 jobs Flex vacation | 151 jobs Parental leave | 124 jobs Wellness | 93 jobs 401(k) matching | 85 jobs Conferences | 49 jobs Relocation support | 43 jobs Fitness / gym | 36 jobs Transparency | 33 jobs Flexible spending account | 25 jobs Gear | 23 jobs

Salary Composition

The salary for an entry-level or junior data scientist typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policies and your individual performance. In tech hubs like Silicon Valley, companies might offer stock options as part of the compensation package, which can be a significant addition to the overall remuneration. In contrast, smaller companies or those in less competitive regions might offer fewer additional incentives. Industry also plays a role; for instance, finance and tech companies often offer higher salaries compared to other sectors.

Increasing Salary

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand, such as expertise in machine learning algorithms, data engineering, or big data technologies. Networking within the industry and seeking mentorship can also provide insights into career advancement opportunities. Additionally, gaining experience in a specific industry can make you more valuable; for example, becoming a domain expert in healthcare data science can open doors to higher-paying roles. Pursuing further education, such as a master's degree or even a Ph.D., can also lead to higher salary prospects, especially in research-intensive roles.

Educational Requirements

Most entry-level data scientist positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree in data science or a related discipline. The educational background should provide a strong foundation in statistical analysis, programming, and data manipulation. Coursework in machine learning, data visualization, and database management is also highly beneficial.

Helpful Certifications

Certifications can enhance your resume and demonstrate your commitment to the field. Some popular certifications include:

• Certified Data Scientist (CDS): Offered by various organizations, this certification covers essential data science skills.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems.
• Microsoft Certified: Azure Data Scientist Associate: Validates your ability to apply data science and machine learning techniques on Azure.
• IBM Data Science Professional Certificate: A comprehensive program that covers data science tools and methodologies.

Required Experience

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects. Experience with data analysis, statistical software (such as R or Python), and data visualization tools (like Tableau or Power BI) is often required. While direct work experience in a professional setting is beneficial, demonstrating your skills through personal projects or contributions to open-source projects can also be valuable.

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