Salary for Mid-level / Intermediate Manager in United States during 2024

Salary details

The average mid-level / intermediate Manager salary lies between USD 104,305 and USD 184,000 in the United States. 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.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 3, 2024

Top 20 Job Tags for Mid-level / Intermediate Manager roles

The three most common job tag items assiciated with mid-level / intermediate Manager job listings are Engineering, Python and SQL. 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 | 3429 jobs Python | 2932 jobs SQL | 2626 jobs Machine Learning | 2408 jobs Computer Science | 2101 jobs Research | 1931 jobs Statistics | 1901 jobs Data management | 1429 jobs R | 1417 jobs Agile | 1312 jobs Data analysis | 1274 jobs Security | 1260 jobs Data Analytics | 1252 jobs Architecture | 1242 jobs Excel | 1207 jobs Testing | 1205 jobs Tableau | 1152 jobs Mathematics | 1103 jobs Power BI | 1055 jobs Finance | 1048 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Manager job listings are Career development, Health care and Flex hours. 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 | 4373 jobs Health care | 2535 jobs Flex hours | 1683 jobs Equity / stock options | 1609 jobs Startup environment | 1531 jobs Competitive pay | 1298 jobs Team events | 1275 jobs Salary bonus | 1102 jobs Flex vacation | 1022 jobs Insurance | 1006 jobs Parental leave | 923 jobs Medical leave | 816 jobs Wellness | 611 jobs 401(k) matching | 523 jobs Transparency | 274 jobs Home office stipend | 246 jobs Conferences | 237 jobs Relocation support | 235 jobs Unlimited paid time off | 193 jobs Gear | 172 jobs

Salary Composition

In the United States, the salary composition for a mid-level/intermediate manager in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, often making up 10% to 20% of the total compensation. Additional remuneration, such as stock options, is more common in larger tech companies and startups, potentially accounting for 5% to 15% of the total package.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets. Industry-wise, tech companies, financial services, and healthcare often offer higher compensation packages compared to other 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 from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your technical skills, especially in emerging AI/ML technologies and tools. Proficiency in programming languages like Python, R, and frameworks like TensorFlow or PyTorch can be advantageous.

• Leadership Development: Strengthen your leadership and management skills. Taking on more responsibilities, leading larger teams, or managing more complex projects can position you for higher roles.

• Networking: Build a strong professional network within the industry. Attend conferences, workshops, and seminars to connect with industry leaders and peers.

• Advanced Education: Pursue further education, such as an MBA or a specialized master's degree in data science or AI, to enhance your qualifications.

• Performance and Negotiation: Consistently deliver high performance and be prepared to negotiate your salary during performance reviews or when taking on new roles.

Educational Requirements

Most mid-level/intermediate manager positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, data science, statistics, or engineering. However, a master's degree is often preferred and can be a significant advantage. Degrees that focus on business analytics or data-driven decision-making are also valuable, especially for roles that require a blend of technical and managerial skills.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.

• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing, building, and productionizing ML models.

• AWS Certified Machine Learning – Specialty: Shows expertise in using AWS services for machine learning.

• Microsoft Certified: Azure AI Engineer Associate: Highlights skills in using Azure AI services.

These certifications can help differentiate you from other candidates and show a commitment to continuous learning.

Required Experience

Typically, a mid-level/intermediate manager in AI/ML/Data Science is expected to have 5 to 8 years of relevant experience. This includes hands-on experience in data analysis, machine learning model development, and project management. Experience in leading teams or projects, as well as a proven track record of delivering successful AI/ML solutions, is highly valued.

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