Salary for Senior-level / Expert Applied Scientist during 2024

Salary details

The average senior-level / expert Applied Scientist salary lies between USD 133,600 and USD 247,000 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: Jan. 19, 2025

Salary trend

Top 20 Job Tags for Senior-level / Expert Applied Scientist roles

The three most common job tag items assiciated with senior-level / expert Applied Scientist job listings are Machine Learning, Engineering 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:

Machine Learning | 760 jobs Engineering | 619 jobs Python | 599 jobs Deep Learning | 551 jobs Statistics | 514 jobs Research | 507 jobs ML models | 487 jobs LLMs | 476 jobs Computer Science | 378 jobs PhD | 316 jobs SQL | 277 jobs Testing | 259 jobs AWS | 255 jobs NLP | 247 jobs Generative AI | 225 jobs TensorFlow | 207 jobs Git | 200 jobs Java | 200 jobs Kubernetes | 198 jobs Docker | 198 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Applied Scientist roles

The three most common job benefits and perks assiciated with senior-level / expert Applied Scientist job listings are Career development, Equity / stock options and Startup environment. 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 | 729 jobs Equity / stock options | 398 jobs Startup environment | 311 jobs Conferences | 245 jobs Competitive pay | 244 jobs Health care | 236 jobs Medical leave | 232 jobs Salary bonus | 230 jobs Flex hours | 168 jobs Parental leave | 139 jobs Flex vacation | 131 jobs Team events | 130 jobs Insurance | 102 jobs 401(k) matching | 67 jobs Flexible spending account | 66 jobs Relocation support | 33 jobs Fitness / gym | 32 jobs Fertility benefits | 21 jobs Transparency | 20 jobs Wellness | 18 jobs

Salary Composition

The salary for a Senior-level or Expert 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 success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can significantly increase the total compensation, especially if the company performs well.

Regional differences also play a crucial 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 competition for talent. Industry-wise, tech companies, financial services, and healthcare often offer higher salaries 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.

Increasing Salary

To increase your salary further from a Senior-level position, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML that is in high demand, such as deep learning, natural language processing, or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of AI or Chief Data Scientist, which typically come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. This can involve taking advanced courses or attending workshops and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level or Expert Applied Scientist roles require at least a Master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. A Ph.D. is often preferred, especially for roles that involve research and development of new algorithms or methodologies. The educational background should include a strong foundation in machine learning, data analysis, and programming.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

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

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

Required Experience

Typically, a Senior-level or Expert Applied Scientist position requires at least 5-10 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects, mentoring junior team members, and contributing to strategic decision-making is also highly valued.

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