Manager Salary in United States during 2024

Salary details

The average Manager salary lies between USD 117,832 and USD 208,000 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 Manager roles

The three most common job tag items assiciated with Manager job listings are Engineering, Python and Machine Learning. 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 | 6782 jobs Python | 5321 jobs Machine Learning | 4989 jobs SQL | 4637 jobs Computer Science | 4239 jobs Research | 3683 jobs Statistics | 3452 jobs Agile | 2660 jobs Architecture | 2633 jobs Data management | 2572 jobs R | 2531 jobs Security | 2459 jobs Testing | 2367 jobs Data Analytics | 2365 jobs Data analysis | 2182 jobs AWS | 2125 jobs Mathematics | 2089 jobs Excel | 2060 jobs Privacy | 2029 jobs Tableau | 1961 jobs

Top 20 Job Perks/Benefits for Manager roles

The three most common job benefits and perks assiciated with 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 | 8310 jobs Health care | 4802 jobs Equity / stock options | 3102 jobs Flex hours | 3095 jobs Startup environment | 2876 jobs Competitive pay | 2614 jobs Team events | 2381 jobs Salary bonus | 2214 jobs Insurance | 1955 jobs Flex vacation | 1923 jobs Medical leave | 1757 jobs Parental leave | 1753 jobs Wellness | 1229 jobs 401(k) matching | 1059 jobs Transparency | 555 jobs Home office stipend | 471 jobs Relocation support | 430 jobs Conferences | 420 jobs Unlimited paid time off | 361 jobs Flexible spending account | 349 jobs

Salary Composition

In the United States, the salary composition for an AI/ML/Data Science Manager can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components:

• Base Salary: This is the fixed annual salary and usually constitutes the largest portion of the total compensation package. In tech hubs like Silicon Valley, New York, or Seattle, the base salary might be higher due to the cost of living and competitive market.

• Bonus: Bonuses can be performance-based or company-wide and are often tied to the achievement of specific goals or milestones. In larger tech companies, bonuses can be a significant part of the compensation, sometimes ranging from 10% to 30% of the base salary.

• Additional Remuneration: This includes stock options, equity, or other long-term incentives, which are common in tech startups and large tech firms. These can be particularly lucrative if the company performs well.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and methodologies. Specializing in niche areas like deep learning, natural language processing, or AI ethics can make you more valuable.

• Leadership Development: Enhance your leadership and management skills. Pursuing executive education programs or leadership workshops can prepare you for higher-level roles.

• Networking: Build a strong professional network within the industry. Attend conferences, join professional organizations, and engage in online communities to increase your visibility and opportunities.

• Performance Excellence: Consistently exceed performance expectations and take on challenging projects that demonstrate your ability to drive results.

Educational Requirements

Most AI/ML/Data Science Manager positions 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 or Ph.D. is often preferred, especially for roles in research-intensive industries or companies. Advanced degrees can provide a deeper understanding of complex algorithms and data analysis techniques, which are crucial for leading AI/ML teams.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your commitment to the field:

• Certified Analytics Professional (CAP): This certification is recognized across industries and validates your ability to transform data into valuable insights.

• AWS Certified Machine Learning – Specialty: This is beneficial if you are working with AWS technologies and want to demonstrate your expertise in building, training, and deploying ML models on AWS.

• Google Professional Machine Learning Engineer: This certification is useful for those working with Google Cloud technologies and focuses on designing, building, and productionizing ML models.

Experience Requirements

Typically, a minimum of 5-10 years of experience in data science, machine learning, or a related field is required. This experience should include hands-on technical work as well as leadership roles where you have managed teams or projects. Experience in a specific industry can also be beneficial, as it provides domain knowledge that can be critical for certain roles.

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