Salary for Entry-level / Junior Applied Scientist during 2023

Salary details

The average entry-level / junior Applied Scientist salary lies between USD 130,760 and USD 213,660 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. 17, 2024

Salary trend

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

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

Machine Learning | 15 jobs Python | 14 jobs Research | 14 jobs Statistics | 14 jobs Computer Science | 14 jobs Computer Vision | 12 jobs Engineering | 12 jobs Java | 12 jobs Robotics | 11 jobs Deep Learning | 9 jobs PhD | 9 jobs Mathematics | 8 jobs R | 3 jobs Data Mining | 3 jobs NLP | 2 jobs PyTorch | 2 jobs Matlab | 2 jobs AWS | 2 jobs Data Analytics | 2 jobs Industrial | 2 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior Applied Scientist job listings are Career development, Conferences and Equity / stock options. 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 | 6 jobs Conferences | 6 jobs Equity / stock options | 5 jobs Flex hours | 1 jobs Startup environment | 1 jobs Team events | 1 jobs

Salary Composition

The salary for an entry-level or junior applied scientist in AI/ML/Data Science 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. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration like stock options is more common in larger tech companies or startups, where equity can be a significant part of the compensation package. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and more substantial equity packages compared to other regions. Industry also plays a role; for instance, finance and healthcare sectors might offer higher bonuses compared to academia or non-profits.

Increasing Salary

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

• Skill Enhancement: Continuously upgrade your skills in high-demand areas such as deep learning, natural language processing, or big data technologies.
• Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open up higher-paying opportunities.
• Networking: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and raises.
• Industry Switch: Consider moving to industries that offer higher compensation for AI/ML roles, such as finance or tech.

Educational Requirements

Most entry-level applied scientist positions require at least a bachelor's degree in a relevant field such as computer science, data science, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and research. These advanced degrees provide a deeper understanding of machine learning algorithms, statistical methods, and data analysis techniques, which are crucial for the role.

Helpful Certificates

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

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer

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

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 programming languages like Python or R, familiarity with machine learning frameworks such as TensorFlow or PyTorch, and hands-on experience with data analysis and visualization tools are often expected. Demonstrating experience through a portfolio of projects or contributions to open-source projects can also be beneficial.

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