Salary for Mid-level / Intermediate Data Manager in United States during 2023

Salary details

The average mid-level / intermediate Data Manager salary lies between USD 73,500 and USD 115,500 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: Dec. 22, 2024

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate Data Manager job listings are Data management, Research and Statistics. 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:

Data management | 78 jobs Research | 65 jobs Statistics | 42 jobs Testing | 41 jobs Data quality | 37 jobs Engineering | 30 jobs GCP | 30 jobs Pharma | 30 jobs Consulting | 28 jobs SQL | 26 jobs Excel | 23 jobs Python | 20 jobs Mathematics | 20 jobs RDBMS | 20 jobs Power BI | 18 jobs Agile | 18 jobs Data analysis | 17 jobs Computer Science | 17 jobs Data governance | 15 jobs Security | 12 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data 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 2023 and the number of open jobs that where offering them during that period:

Career development | 72 jobs Health care | 55 jobs Flex hours | 36 jobs Startup environment | 34 jobs Competitive pay | 30 jobs Flex vacation | 20 jobs Team events | 17 jobs 401(k) matching | 13 jobs Parental leave | 12 jobs Insurance | 12 jobs Medical leave | 10 jobs Salary bonus | 9 jobs Equity / stock options | 7 jobs Wellness | 6 jobs Home office stipend | 5 jobs Gear | 3 jobs Relocation support | 3 jobs Unlimited paid time off | 3 jobs Fitness / gym | 2 jobs Conferences | 1 jobs

Salary Composition

In the United States, the salary for a Mid-level/Intermediate Data Manager in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in tech companies and startups, especially in regions like Silicon Valley. In larger corporations, profit-sharing or 401(k) matching might be more prevalent. The composition can also vary by industry, with tech and finance sectors generally offering higher bonuses and stock options compared to healthcare or education.

Increasing Salary

To increase your salary from a Mid-level Data Manager position, consider the following steps:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML and data science. Specializing in high-demand areas like deep learning, natural language processing, or big data analytics can make you more valuable.
• Advanced Education: Pursuing a master's degree or a Ph.D. in a related field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into a leadership or managerial role, such as a Data Science Manager or Director of Data Science, can significantly increase your earning potential.
• Industry Change: Moving to a higher-paying industry, such as finance or tech, can also result in a salary increase.
• Networking and Visibility: Building a strong professional network and increasing your visibility in the field through conferences, publications, or speaking engagements can lead to better job offers.

Educational Requirements

Most Mid-level Data Manager positions require at least a bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics, or Engineering. However, a master's degree in Data Science, Business Analytics, or a related discipline is often preferred and can provide a competitive edge. Some roles may also value interdisciplinary degrees that combine technical skills with business acumen.

Helpful Certifications

Certifications can enhance your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• SAS Certified Data Scientist

These certifications can validate your skills and knowledge, making you a more attractive candidate for higher-level positions.

Experience Requirements

Typically, a Mid-level Data Manager role requires 3 to 5 years of experience in data management, analytics, or a related field. Experience with data warehousing, data modeling, and proficiency in programming languages such as Python, R, or SQL is often expected. Familiarity with machine learning frameworks and tools like TensorFlow, PyTorch, or Scikit-learn is also advantageous.

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