Applied Scientist Salary in 2023

Salary details

The average Applied Scientist salary lies between USD 136,000 and USD 222,200 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

Salary trend

Top 20 Job Tags for Applied Scientist roles

The three most common job tag items assiciated with Applied Scientist job listings are Machine Learning, Research and Python. 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 | 235 jobs Research | 189 jobs Python | 182 jobs Engineering | 157 jobs PhD | 140 jobs Deep Learning | 132 jobs Java | 127 jobs ML models | 120 jobs Statistics | 116 jobs Computer Science | 110 jobs TensorFlow | 85 jobs NLP | 76 jobs Computer Vision | 75 jobs PyTorch | 60 jobs Mathematics | 60 jobs Spark | 59 jobs AWS | 57 jobs R | 54 jobs Reinforcement Learning | 54 jobs Data Mining | 45 jobs

Top 20 Job Perks/Benefits for Applied Scientist roles

The three most common job benefits and perks assiciated with Applied Scientist job listings are Career development, Equity / stock options and Conferences. 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 | 201 jobs Equity / stock options | 161 jobs Conferences | 96 jobs Startup environment | 82 jobs Health care | 64 jobs Competitive pay | 64 jobs Flex hours | 55 jobs Salary bonus | 54 jobs Flex vacation | 29 jobs Team events | 28 jobs Parental leave | 21 jobs Medical leave | 20 jobs Insurance | 17 jobs 401(k) matching | 14 jobs Transparency | 12 jobs Home office stipend | 10 jobs Wellness | 9 jobs Relocation support | 8 jobs Unlimited paid time off | 8 jobs Gear | 6 jobs

Salary Composition for an Applied Scientist in AI/ML/Data Science

The salary for an Applied Scientist in AI/ML/Data Science typically comprises 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 forms the largest part of the total compensation package. Performance bonuses can vary significantly depending on the company's performance and individual contributions, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies and startups, providing long-term incentives aligned with company growth.

Regional differences also play a significant role. For instance, salaries in tech hubs like Silicon Valley or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies, finance, and healthcare often offer higher compensation packages compared to academia or non-profit sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Steps to Increase Salary from an Applied Scientist Position

To increase your salary from an Applied Scientist position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing further education, such as a Ph.D. or specialized certifications, can position you for higher-level roles and salary brackets.

• Leadership Roles: Transitioning into leadership or managerial roles can significantly increase your earning potential. This might involve leading a team of scientists or managing cross-functional projects.

• Networking and Visibility: Building a strong professional network and increasing your visibility in the industry through conferences, publications, or speaking engagements can open up higher-paying opportunities.

• Negotiation Skills: Improving your negotiation skills can help you secure better compensation packages during job offers or performance reviews.

Educational Requirements for an Applied Scientist Role

Most Applied Scientist roles in AI/ML/Data Science require at least a master's degree in a relevant field such as computer science, data science, statistics, or engineering. A Ph.D. is often preferred, especially for research-intensive positions, as it demonstrates a deep understanding of complex algorithms and the ability to conduct independent research. Strong mathematical and statistical skills are essential, and coursework in machine learning, data mining, and artificial intelligence is highly beneficial.

Helpful Certifications for an Applied Scientist

While not always mandatory, certain certifications can enhance your profile and demonstrate expertise in specific areas. Some valuable certifications include:

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

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

Experience Required for an Applied Scientist Role

Typically, an Applied Scientist role requires several years of experience in data science or machine learning. This experience should include hands-on work with data analysis, model development, and deployment. Experience in a specific industry, such as finance, healthcare, or technology, can be advantageous, as it provides domain knowledge that can be critical for certain roles. Additionally, experience with programming languages like Python or R, and familiarity with machine learning frameworks such as TensorFlow or PyTorch, is often required.

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