Salary for Senior-level / Expert Data Modeler in United States during 2023

Salary details

The average senior-level / expert Data Modeler salary lies between USD 105,200 and USD 160,000 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. 17, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Modeler roles

The three most common job tag items assiciated with senior-level / expert Data Modeler job listings are SQL, Engineering and Python. 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:

SQL | 41 jobs Engineering | 33 jobs Python | 27 jobs Azure | 24 jobs Consulting | 21 jobs Security | 21 jobs ETL | 19 jobs Pipelines | 19 jobs Data Warehousing | 17 jobs Testing | 17 jobs Architecture | 17 jobs Oracle | 16 jobs Data pipelines | 16 jobs Statistics | 16 jobs AWS | 15 jobs Big Data | 14 jobs Spark | 14 jobs Data analysis | 14 jobs APIs | 14 jobs Data warehouse | 14 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Modeler roles

The three most common job benefits and perks assiciated with senior-level / expert Data Modeler job listings are Career development, Health care and Startup environment. 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 | 30 jobs Health care | 27 jobs Startup environment | 16 jobs 401(k) matching | 14 jobs Flex hours | 10 jobs Equity / stock options | 7 jobs Team events | 7 jobs Salary bonus | 7 jobs Competitive pay | 6 jobs Insurance | 5 jobs Flex vacation | 4 jobs Relocation support | 2 jobs Medical leave | 2 jobs Parental leave | 1 jobs Flat hierarchy | 1 jobs Gear | 1 jobs Transparency | 1 jobs Conferences | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Modeler can vary significantly based on region, industry, and company size. Typically, the salary package includes a fixed base salary, which constitutes the majority of the total compensation. This base salary can range from 70% to 85% of the total package. Bonuses, which can be performance-based or company-wide, often make up 10% to 20% of the total compensation. Additional remuneration may include stock options, especially in tech companies, and other benefits such as health insurance, retirement contributions, and paid time off. 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 a Senior-level Data Modeler position, consider the following strategies:

• Specialization: Develop expertise in a niche area of data modeling or machine learning that is in high demand, such as deep learning, natural language processing, or big data technologies.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Data Science, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and data science. This can involve taking advanced courses or attending workshops and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level Data Modeler positions require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data analysis and modeling. Advanced degrees provide a deeper understanding of theoretical concepts and practical applications, which are crucial for high-level data modeling tasks.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. 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 in specific tools and platforms, making you a more attractive candidate for senior roles.

Required Experience

Typically, a Senior-level Data Modeler is expected to have at least 5 to 10 years of experience in data modeling, data analysis, or a related field. This experience should include hands-on work with data modeling tools, statistical analysis, and machine learning algorithms. Experience in leading projects or teams, as well as a proven track record of delivering data-driven solutions, is also highly valued.

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