Salary for Entry-level / Junior Research Scientist during 2024

Salary details

The average entry-level / junior Research Scientist salary lies between USD 137,750 and USD 250,000 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: Nov. 24, 2024

Salary trend

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

The three most common job tag items assiciated with entry-level / junior Research Scientist job listings are Research, Machine Learning and Python. 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:

Research | 469 jobs Machine Learning | 390 jobs Python | 380 jobs PhD | 365 jobs Computer Science | 285 jobs Computer Vision | 270 jobs NeurIPS | 266 jobs Deep Learning | 252 jobs PyTorch | 250 jobs ICLR | 238 jobs NLP | 231 jobs Physics | 225 jobs ICML | 221 jobs Engineering | 203 jobs VR | 194 jobs LLMs | 172 jobs Open Source | 156 jobs TensorFlow | 152 jobs Mathematics | 136 jobs Generative AI | 123 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior Research Scientist job listings are Career development, Conferences and Health care. 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 | 399 jobs Conferences | 303 jobs Health care | 283 jobs Equity / stock options | 246 jobs Salary bonus | 146 jobs Medical leave | 116 jobs Flex vacation | 100 jobs Insurance | 95 jobs Parental leave | 91 jobs Startup environment | 85 jobs 401(k) matching | 83 jobs Flexible spending account | 79 jobs Team events | 55 jobs Flex hours | 35 jobs Transparency | 35 jobs Competitive pay | 23 jobs Wellness | 16 jobs Fitness / gym | 5 jobs Relocation support | 5 jobs Snacks / Drinks | 3 jobs

Salary Composition

The salary for an entry-level or junior research scientist in AI/ML/Data Science typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly depending on the region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with generous bonuses or stock options. Large tech companies often provide comprehensive benefits packages, including health insurance, retirement plans, and other perks, which can add significant value to the overall compensation package.

Increasing Salary

To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand. Pursuing advanced degrees, such as a master's or Ph.D., can also open doors to higher-paying roles. Networking within the industry and seeking mentorship can provide insights into career advancement opportunities. Additionally, gaining experience in high-impact projects or transitioning to roles with more responsibility, such as team lead or project manager, can lead to salary increases. Staying updated with the latest trends and technologies in AI/ML can also make you more valuable to employers.

Educational Requirements

Most entry-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master's degree or Ph.D., especially for research-focused roles. A strong academic background in machine learning, data analysis, and programming is essential. Coursework or projects that demonstrate practical experience with AI/ML tools and techniques can also be beneficial.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your commitment to the field. Certifications from recognized institutions, such as the Certified Machine Learning Professional (CMLP) or the TensorFlow Developer Certificate, can be advantageous. Additionally, completing online courses from platforms like Coursera, edX, or Udacity that offer certificates in AI/ML can also be helpful. These certifications can validate your skills and knowledge to potential employers.

Required Experience

For entry-level roles, 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 programming languages such as Python or R, and familiarity with machine learning frameworks like TensorFlow or PyTorch, is often expected. Demonstrating experience in data analysis, model development, and problem-solving through personal or academic projects can also be beneficial.

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