Salary for Mid-level / Intermediate Applied Scientist during 2024

Salary details

The average mid-level / intermediate 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. 15, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Applied Scientist roles

The three most common job tag items assiciated with mid-level / intermediate Applied Scientist job listings are Machine Learning, Python and PhD. 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 | 175 jobs Python | 159 jobs PhD | 147 jobs Research | 137 jobs Java | 133 jobs Deep Learning | 99 jobs Engineering | 95 jobs Data Mining | 92 jobs LLMs | 83 jobs Computer Science | 80 jobs ML models | 71 jobs Linux | 69 jobs Statistics | 66 jobs NLP | 62 jobs Generative AI | 59 jobs PyTorch | 51 jobs TensorFlow | 45 jobs Security | 40 jobs AWS | 39 jobs CX | 39 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Applied Scientist roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 2024 and the number of open jobs that where offering them during that period:

Career development | 161 jobs Conferences | 108 jobs Equity / stock options | 102 jobs Startup environment | 44 jobs Medical leave | 37 jobs Health care | 30 jobs Team events | 30 jobs Flex hours | 19 jobs Parental leave | 13 jobs Flex vacation | 6 jobs Insurance | 6 jobs Relocation support | 5 jobs Competitive pay | 4 jobs Salary bonus | 4 jobs Home office stipend | 4 jobs 401(k) matching | 3 jobs Flexible spending account | 3 jobs Wellness | 1 jobs Gear | 1 jobs Fitness / gym | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate 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 composition can vary significantly depending on the region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with generous bonuses or stock options. In larger companies, you might find a more structured bonus system tied to performance metrics, while startups might offer more equity as part of the compensation package.

Steps to Increase Salary

To increase your salary from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Leadership Roles: Aim for leadership or managerial roles, which typically come with higher pay. This might involve leading a team of data scientists or managing projects.
• Networking: Build a strong professional network. Engaging with industry peers can open up opportunities for higher-paying positions.
• Publications and Patents: Contributing to research papers or obtaining patents can enhance your reputation and lead to salary increases.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most mid-level applied scientist roles require at least a master's degree in a relevant field such as computer science, data science, statistics, or a related discipline. Some positions might require a Ph.D., especially in research-intensive roles or at top-tier companies. A strong academic background provides a solid foundation in the theoretical aspects of AI/ML, which is crucial for developing and implementing complex models.

Helpful Certifications

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

• 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 and knowledge in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level applied scientist role requires 3-5 years of experience in AI/ML or data science. This experience should include hands-on work with machine learning models, data analysis, and possibly some project management. Experience in deploying models in production environments and working with cross-functional teams is also highly valued.

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