Salary for Entry-level / Junior Data Scientist during 2023

Salary details

The average entry-level / junior Data Scientist salary lies between USD 63,200 and USD 130,001 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 2023 and the number of open jobs that where associated with them during that period:

Python | 508 jobs Machine Learning | 426 jobs SQL | 309 jobs Statistics | 304 jobs R | 288 jobs Engineering | 268 jobs Computer Science | 236 jobs Mathematics | 205 jobs Research | 177 jobs Big Data | 135 jobs Data analysis | 121 jobs ML models | 110 jobs Deep Learning | 101 jobs TensorFlow | 100 jobs Testing | 96 jobs Pandas | 91 jobs Agile | 91 jobs NLP | 90 jobs R&D | 88 jobs PyTorch | 84 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 2023 and the number of open jobs that where offering them during that period:

Career development | 350 jobs Health care | 141 jobs Flex hours | 133 jobs Startup environment | 127 jobs Competitive pay | 95 jobs Team events | 89 jobs Insurance | 84 jobs Flex vacation | 74 jobs Equity / stock options | 72 jobs Salary bonus | 50 jobs Parental leave | 47 jobs Medical leave | 41 jobs 401(k) matching | 33 jobs Conferences | 24 jobs Wellness | 16 jobs Home office stipend | 15 jobs Gear | 14 jobs Relocation support | 13 jobs Fitness / gym | 12 jobs Lunch / meals | 11 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. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and paid time off. The composition can vary by region, with tech hubs like San Francisco or New York offering higher base salaries but potentially less in bonuses compared to other regions. Industry also plays a role; for instance, finance and tech industries might offer higher bonuses compared to academia or non-profits. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and smaller startups offering equity as part of the compensation.

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 cloud computing. Pursuing a master's degree or further education in data science or a related field can also enhance your qualifications. Networking within the industry and seeking mentorship can provide insights into career advancement opportunities. Additionally, gaining experience by working on diverse projects or taking on leadership roles within your team can demonstrate your value to your employer. Transitioning to a higher-paying industry or relocating to a region with higher salary standards can also be effective strategies.

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. Some positions may prefer or require a master's degree in data science or a related discipline. Coursework in machine learning, data analysis, and programming languages like Python or R is often essential. A strong foundation in statistics and mathematics is also crucial, as these are the core skills needed for data analysis and model building.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise. Popular certifications include:

• Certified Analytics Professional (CAP)
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning – Specialty

These certifications can validate your skills in data analysis, machine learning, and cloud computing, making you a more competitive candidate.

Experience Requirements

For an entry-level data scientist role, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects during your studies. Experience with data manipulation, statistical analysis, and machine learning projects is often expected. Familiarity with data visualization tools and experience in programming with languages like Python, R, or SQL is also beneficial. While extensive professional experience is not required, demonstrating your ability to apply theoretical knowledge to real-world problems is crucial.

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