Salary for Senior-level / Expert Applied Scientist during 2023

Salary details

The average senior-level / expert 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: Nov. 17, 2024

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, 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 | 180 jobs Research | 142 jobs Python | 132 jobs Engineering | 127 jobs PhD | 108 jobs ML models | 103 jobs Deep Learning | 100 jobs Java | 92 jobs Computer Science | 84 jobs Statistics | 83 jobs TensorFlow | 67 jobs NLP | 63 jobs Spark | 58 jobs R | 45 jobs Computer Vision | 45 jobs PyTorch | 43 jobs Mathematics | 42 jobs Reinforcement Learning | 42 jobs AWS | 41 jobs Pipelines | 35 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 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 | 159 jobs Equity / stock options | 130 jobs Conferences | 69 jobs Startup environment | 58 jobs Competitive pay | 54 jobs Salary bonus | 52 jobs Flex hours | 50 jobs Health care | 49 jobs Flex vacation | 25 jobs Team events | 22 jobs Parental leave | 17 jobs Medical leave | 15 jobs 401(k) matching | 12 jobs Transparency | 9 jobs Home office stipend | 9 jobs Unlimited paid time off | 8 jobs Wellness | 7 jobs Insurance | 7 jobs Gear | 6 jobs Relocation support | 6 jobs

Salary Composition

The salary for a Senior-level or Expert Applied Scientist in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20% of the salary. Additional remuneration may include stock options, especially in tech companies, which can significantly increase total earnings. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and more substantial stock options. Industry also plays a role; for instance, finance and healthcare sectors might offer higher bonuses, while smaller startups might compensate with more equity. Company size can influence the package, with larger companies typically providing more structured and predictable bonuses and benefits.

Increasing Salary Further

To increase your salary beyond the median for this role, consider pursuing leadership positions such as a Principal Scientist or Head of Data Science. These roles often come with higher compensation and more significant responsibilities. Specializing in high-demand areas like deep learning, natural language processing, or AI ethics can also make you more valuable. Networking within industry circles and attending conferences can open up opportunities for higher-paying roles. Additionally, negotiating your salary during job offers or performance reviews by showcasing your impact on business outcomes can lead to higher compensation.

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 cutting-edge research or complex problem-solving. The educational background should include a strong foundation in machine learning, data analysis, and programming languages like Python or R. Coursework or research experience in AI/ML algorithms, data structures, and statistical modeling is highly beneficial.

Helpful Certificates

While not always mandatory, certain certifications can enhance your profile. Certificates like the Certified Data Scientist (CDS) or TensorFlow Developer Certificate can demonstrate your expertise in specific tools and methodologies. Online platforms like Coursera, edX, and Udacity offer specialized courses and nanodegrees in AI and machine learning that can be valuable. Certifications in cloud platforms like AWS Certified Machine Learning or Google Cloud Professional Data Engineer can also be advantageous, given the increasing reliance on cloud-based solutions.

Required Experience

Typically, a Senior-level or Expert Applied Scientist is expected to have 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 collaborating with cross-functional teams is often required. A proven track record of deploying AI/ML solutions that drive business value is crucial. Experience in a specific industry, such as finance, healthcare, or technology, can also be beneficial.

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