Salary for Senior-level / Expert Data Modeler during 2023

Salary details

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

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

The salary for a Senior-level or Expert Data Modeler in AI/ML/Data Science typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary often constitutes the majority of the total compensation package, usually around 70-80%. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the total salary. Additional remuneration, such as stock options, is more common in tech companies and startups, potentially making up 5-10% of the total package. Regional differences also play a role; for instance, salaries in tech hubs like Silicon Valley or New York City tend to be higher due to the cost of living and competitive job market. In contrast, smaller companies or those in less competitive regions might offer lower base salaries but compensate with higher equity stakes or bonuses.

Increasing Salary

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

• Specialization: Develop expertise in niche areas of AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand.
• 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 through courses, 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 modeling and advanced machine learning techniques. These 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 Data Scientist (CDS)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

These certifications 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 5-10 years of experience in data science or related fields. This experience should include hands-on work with data modeling, machine learning algorithms, and data analysis. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued. Demonstrated success in deploying data models that drive business decisions or product development is a significant advantage.

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