Salary for Senior-level / Expert Manager during 2024
💰 The median Salary for Senior-level / Expert Manager during 2024 is USD 178,445
✏️ This salary info is based on 1060 individual salaries reported during 2024
Salary details
The average senior-level / expert Manager salary lies between USD 137,600 and USD 220,000 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.
- Job title
- Manager
- Experience
- Senior-level / Expert
- Region
- global/worldwide
- Salary year
- 2024
- Sample size
- 1060
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Top 20 Job Tags for Senior-level / Expert Manager roles
The three most common job tag items assiciated with senior-level / expert Manager job listings are Engineering, Machine Learning 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:
Engineering | 3766 jobs Machine Learning | 2931 jobs Python | 2627 jobs Computer Science | 2338 jobs SQL | 2184 jobs Research | 1920 jobs Statistics | 1723 jobs Architecture | 1584 jobs Agile | 1461 jobs Security | 1364 jobs Testing | 1298 jobs AWS | 1231 jobs Data management | 1228 jobs R | 1212 jobs Data Analytics | 1194 jobs Privacy | 1117 jobs Mathematics | 1073 jobs Azure | 1025 jobs Data analysis | 971 jobs Pipelines | 918 jobsTop 20 Job Perks/Benefits for Senior-level / Expert Manager roles
The three most common job benefits and perks assiciated with senior-level / expert Manager job listings are Career development, Health care 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 | 4335 jobs Health care | 2410 jobs Equity / stock options | 1696 jobs Flex hours | 1493 jobs Startup environment | 1490 jobs Competitive pay | 1384 jobs Salary bonus | 1256 jobs Team events | 1184 jobs Medical leave | 1038 jobs Insurance | 1009 jobs Flex vacation | 974 jobs Parental leave | 922 jobs Wellness | 612 jobs 401(k) matching | 585 jobs Transparency | 319 jobs Home office stipend | 259 jobs Relocation support | 220 jobs Flexible spending account | 206 jobs Conferences | 201 jobs Travel | 185 jobsSalary Composition
The salary for a Senior-level/Expert Manager 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 composition can vary significantly based on region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but bonuses and stock options can also form a substantial part of the total compensation package. In contrast, companies in regions with a lower cost of living might offer a lower base salary but compensate with other benefits. Industries such as finance or healthcare might offer higher bonuses due to the critical nature of data-driven decision-making in these fields. Larger companies often provide more comprehensive benefits and bonuses compared to startups, which might offer more equity to compensate for lower base salaries.
Increasing Salary Further
To increase your salary from this position, consider the following strategies:
- Specialization: Develop expertise in a niche area of AI/ML that is in high demand, such as natural language processing or computer vision.
- Leadership Skills: Enhance your leadership and management skills to take on more significant responsibilities or move into executive roles.
- Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
- Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and valuable to employers.
- Negotiation: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.
Educational Requirements
Most senior-level positions in AI/ML/Data Science require at least a master's degree in a related field such as computer science, data science, statistics, or engineering. A Ph.D. can be advantageous, especially for roles that involve research or developing new algorithms. Additionally, a strong foundation in mathematics and statistics is often essential.
Helpful Certificates
While not always mandatory, certain certifications can enhance your credentials 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
Typically, a senior-level manager in AI/ML/Data Science is expected to have at least 8-10 years of experience in the field. This experience should include hands-on work with data analysis, machine learning model development, and project management. Experience leading teams and managing projects is crucial, as these roles often involve overseeing the work of other data scientists and engineers.
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