Salary for Entry-level / Junior Machine Learning Scientist in United States during 2024

Salary details

The average entry-level / junior Machine Learning Scientist salary lies between USD 106,590 and USD 208,800 in the United States. 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.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 22, 2024

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

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

Machine Learning | 31 jobs Python | 26 jobs Engineering | 20 jobs PhD | 20 jobs Research | 19 jobs Computer Science | 19 jobs Security | 16 jobs Deep Learning | 15 jobs SQL | 13 jobs AWS | 13 jobs ML models | 13 jobs Statistics | 13 jobs NLP | 12 jobs PyTorch | 12 jobs Spark | 12 jobs Java | 11 jobs Testing | 10 jobs Architecture | 10 jobs Physics | 10 jobs TensorFlow | 9 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior Machine Learning Scientist job listings are Career development, Health care and Insurance. 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 | 30 jobs Health care | 23 jobs Insurance | 15 jobs Parental leave | 14 jobs Equity / stock options | 13 jobs Flex vacation | 13 jobs Medical leave | 13 jobs Team events | 12 jobs Wellness | 11 jobs Flex hours | 10 jobs 401(k) matching | 9 jobs Startup environment | 8 jobs Conferences | 7 jobs Competitive pay | 6 jobs Salary bonus | 6 jobs Fitness / gym | 5 jobs Relocation support | 4 jobs Flexible spending account | 3 jobs Home office stipend | 1 jobs Fertility benefits | 1 jobs

Salary Composition

The salary for an entry-level or junior machine learning scientist in the United States typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. 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 policy and individual performance, often ranging from 5% to 15% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can be a significant part of the total compensation, especially in regions like Silicon Valley. In smaller companies or non-tech industries, the compensation might lean more heavily on the base salary with fewer bonuses or stock options.

Increasing Salary

To increase your salary from an entry-level position, consider the following steps:

• Skill Enhancement: Continuously update your skills in the latest machine learning techniques and tools. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in a related field can open up higher-paying opportunities.
• Networking: Building a strong professional network can lead to better job opportunities and salary negotiations.
• Performance and Impact: Demonstrating significant contributions to projects and showcasing your impact on the company’s success can justify a salary increase.
• Industry Transition: Moving to industries with higher pay scales, such as finance or tech, can also result in a salary boost.

Educational Requirements

Most entry-level machine learning scientist positions require at least a bachelor's degree in computer science, mathematics, statistics, or a related field. However, a master's degree is often preferred and can make candidates more competitive. Coursework in machine learning, data mining, artificial intelligence, and statistical analysis is particularly beneficial. Some roles may also require knowledge of programming languages such as Python, R, or Java.

Helpful Certificates

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

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications can validate your skills and knowledge in specific platforms and tools, making you more attractive to potential employers.

Experience Requirements

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, projects, or research during your academic career. Experience with machine learning frameworks (like TensorFlow or PyTorch), data analysis, and programming is often expected. While direct industry experience might not be necessary, demonstrating hands-on experience through personal projects or contributions to open-source projects can be advantageous.

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