Salary for Senior-level / Expert Data Modeler in United States during 2024

Salary details

The average senior-level / expert Data Modeler salary lies between USD 112,000 and USD 151,800 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. 24, 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, Architecture and Engineering. 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:

SQL | 139 jobs Architecture | 98 jobs Engineering | 84 jobs Computer Science | 79 jobs Security | 76 jobs ETL | 74 jobs Data governance | 67 jobs Data management | 58 jobs Data Warehousing | 57 jobs Data quality | 56 jobs Agile | 54 jobs Snowflake | 51 jobs Azure | 48 jobs AWS | 47 jobs Data warehouse | 46 jobs NoSQL | 45 jobs Data analysis | 41 jobs Python | 40 jobs Oracle | 37 jobs RDBMS | 37 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 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 | 91 jobs Health care | 68 jobs Flex hours | 36 jobs Competitive pay | 36 jobs Team events | 28 jobs Insurance | 27 jobs Startup environment | 24 jobs Equity / stock options | 22 jobs Flex vacation | 16 jobs 401(k) matching | 14 jobs Salary bonus | 14 jobs Wellness | 13 jobs Relocation support | 11 jobs Transparency | 7 jobs Medical leave | 6 jobs Parental leave | 5 jobs Fitness / gym | 4 jobs Flexible spending account | 4 jobs Gear | 2 jobs Lunch / meals | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Modeler can vary significantly based on factors such as region, industry, and company size. Typically, the salary package is divided into three main components: base salary, bonuses, and additional remuneration.

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

• Bonuses: These are performance-based and can vary widely. In industries like finance or tech, bonuses can be substantial, sometimes making up 10-20% of the total compensation package.

• Additional Remuneration: This includes stock options, profit sharing, and other benefits such as health insurance, retirement plans, and paid time off. Larger companies or those in the tech industry often offer stock options as a significant part of the compensation package.

Increasing Salary

To increase your salary further from a Senior-level Data Modeler position, consider the following strategies:

• Specialize in Niche Areas: Developing expertise in emerging areas like deep learning, natural language processing, or AI ethics can make you more valuable.

• Leadership Roles: Transitioning into managerial or leadership roles can significantly boost your earning potential. This might involve leading a team of data scientists or overseeing large-scale projects.

• Continuous Learning: Stay updated with the latest tools and technologies in AI/ML. Attending workshops, conferences, and pursuing advanced certifications can enhance your skill set and marketability.

• Networking: Building a strong professional network can open up opportunities for higher-paying positions. Engage with industry groups, attend meetups, and connect with peers on platforms like LinkedIn.

Educational Requirements

For a Senior-level Data Modeler position, most employers require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for expert-level roles. Advanced degrees provide a deeper understanding of complex algorithms and data structures, 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:

• 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 cloud-based data solutions.

• TensorFlow Developer Certificate: Useful for those focusing on deep learning and neural networks.

• Data Science Council of America (DASCA) Certifications: These are well-regarded in the data science community.

Required Experience

Typically, a Senior-level Data Modeler is expected to have at least 5-10 years of experience in data science or related fields. This experience should include hands-on work with data modeling, statistical analysis, and machine learning algorithms. Experience in leading projects or teams is also highly valued, as it demonstrates your ability to manage complex tasks and collaborate effectively.

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