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

Salary details

The average entry-level / junior Machine Learning Scientist salary lies between USD 98,300 and USD 208,800 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. 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 typically consists of a base salary, performance bonuses, and 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 other benefits like health insurance, retirement plans, and paid time off.

The composition can vary based on region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and stock options due to the high cost of living and competitive job market. In contrast, companies in smaller cities or less competitive markets might offer lower base salaries but compensate with other benefits. Larger companies often have more structured compensation packages with clear bonus structures, while startups might offer more equity as part of the compensation.

Increasing Salary

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

• Skill Development: Continuously improve your technical skills, especially in high-demand areas like deep learning, natural language processing, or computer vision. Mastering new tools and technologies can make you more valuable to your employer.

• Advanced Education: Pursuing a master's or Ph.D. in a related field can open up higher-level positions and increase your earning potential.

• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and connecting with peers and mentors. Networking can lead to new job opportunities and salary negotiations.

• Performance and Impact: Demonstrate your value by taking on challenging projects, showing leadership potential, and contributing to the company’s success. Document your achievements and be prepared to discuss them during performance reviews.

• Industry Switch: Some industries, like finance or healthcare, may offer higher salaries for machine learning roles compared to others. Consider switching industries if you have the relevant skills and interest.

Educational Requirements

Most entry-level machine learning scientist positions require at least a bachelor's degree in a related field such as computer science, data science, mathematics, or statistics. However, many employers prefer candidates with a master's degree or even a Ph.D., especially for roles that involve complex problem-solving and research. Coursework in machine learning, artificial intelligence, data analysis, and programming is highly beneficial.

Helpful Certificates

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

• Google Professional Machine Learning Engineer: Validates your ability to design, build, and productionize ML models on Google Cloud.

• AWS Certified Machine Learning – Specialty: Demonstrates your ability to build, train, tune, and deploy machine learning models on AWS.

• Microsoft Certified: Azure AI Engineer Associate: Shows proficiency in using Azure AI services to build and integrate AI solutions.

• TensorFlow Developer Certificate: Proves your ability to use TensorFlow to build and train models.

These certifications can be particularly useful if you are targeting roles that require specific platform expertise.

Experience Requirements

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, academic projects, or personal projects. Experience with programming languages like Python or R, familiarity with machine learning frameworks such as TensorFlow or PyTorch, and a solid understanding of data manipulation and analysis are often expected.

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