Salary for Senior-level / Expert Encounter Data Management Professional in United States during 2024

Salary details

The average senior-level / expert Encounter Data Management Professional salary lies between USD 69,800 and USD 96,200 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. 17, 2024

Top 20 Job Tags for Senior-level / Expert Encounter Data Management Professional roles

The three most common job tag items assiciated with senior-level / expert Encounter Data Management Professional job listings are Data management, Excel 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:

Data management | 6 jobs Excel | 5 jobs SQL | 2 jobs Finance | 2 jobs Data analysis | 2 jobs Python | 1 jobs Research | 1 jobs Security | 1 jobs Power BI | 1 jobs Databricks | 1 jobs Bigtable | 1 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Encounter Data Management Professional roles

The three most common job benefits and perks assiciated with senior-level / expert Encounter Data Management Professional job listings are Parental leave, Wellness and Health care. 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:

Parental leave | 6 jobs Wellness | 6 jobs Health care | 6 jobs Competitive pay | 6 jobs Medical leave | 6 jobs Insurance | 6 jobs Salary bonus | 6 jobs 401(k) matching | 1 jobs Career development | 1 jobs Gear | 1 jobs Startup environment | 1 jobs Team events | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Encounter Data Management Professional in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary package includes a fixed base salary, which forms the bulk of the compensation. This base salary can range from 70% to 85% of the total compensation package. Bonuses are often performance-based and can account for 10% to 20% of the total salary, depending on the company's profitability and individual performance metrics. Additional remuneration may include stock options, especially in tech companies or startups, and other benefits such as health insurance, retirement contributions, and professional development allowances. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, salaries tend to be higher to compensate for living expenses. Similarly, larger companies or those in competitive industries like finance or technology may offer more lucrative packages.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or big data analytics can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open doors to higher-paying roles.
• Leadership Roles: Transitioning into managerial or leadership positions can significantly boost your salary.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Certifications: Obtaining relevant certifications can demonstrate your expertise and commitment to the field, potentially leading to salary increases.

Educational Requirements

Most senior-level 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. Some roles may even require a Ph.D., especially in research-intensive positions or at top-tier companies. A strong educational background provides a solid foundation in the theoretical and practical aspects of data management and analysis.

Helpful Certifications

Several certifications can enhance your qualifications for a senior-level role in data management:

• Certified Data Management Professional (CDMP): This certification demonstrates expertise in data management principles and practices.
• AWS Certified Machine Learning – Specialty: Useful for those working with AWS services in AI/ML projects.
• Google Professional Data Engineer: Validates your ability to design, build, and manage data processing systems.
• Microsoft Certified: Azure Data Scientist Associate: Focuses on using Azure services for data science solutions.

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.

Experience Requirements

Typically, a senior-level position in this field requires at least 5 to 10 years of relevant experience. This experience should include hands-on work with data management, analysis, and AI/ML projects. Experience in leading teams, managing projects, and working with cross-functional teams is also highly valued. Demonstrated success in previous roles, such as improving data processes or implementing successful AI/ML solutions, can be crucial in securing a senior position.

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