Data Modeler Salary in 2023

Salary details

The average Data Modeler salary lies between USD 100,000 and USD 155,000 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 Data Modeler roles

The three most common job tag items assiciated with 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 | 55 jobs Engineering | 45 jobs Python | 34 jobs Architecture | 30 jobs Security | 28 jobs Azure | 27 jobs Consulting | 25 jobs Data warehouse | 23 jobs ETL | 22 jobs Big Data | 21 jobs Oracle | 21 jobs Machine Learning | 20 jobs Data analysis | 20 jobs AWS | 19 jobs Pipelines | 19 jobs Computer Science | 19 jobs Data Warehousing | 18 jobs Testing | 18 jobs Statistics | 17 jobs Data quality | 17 jobs

Top 20 Job Perks/Benefits for Data Modeler roles

The three most common job benefits and perks assiciated with 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 | 43 jobs Health care | 35 jobs Startup environment | 18 jobs 401(k) matching | 16 jobs Flex hours | 15 jobs Team events | 10 jobs Equity / stock options | 9 jobs Salary bonus | 9 jobs Flex vacation | 7 jobs Competitive pay | 7 jobs Insurance | 5 jobs Parental leave | 3 jobs Medical leave | 3 jobs Wellness | 2 jobs Fitness / gym | 2 jobs Transparency | 2 jobs Relocation support | 2 jobs Flat hierarchy | 1 jobs Travel | 1 jobs Gear | 1 jobs

Salary Composition

The salary composition for a Data Modeler in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, the base salary might be higher to compensate for living expenses.

• Bonuses: These can be performance-based or company-wide bonuses. In tech-heavy industries, bonuses might be tied to project completion, company performance, or individual performance metrics. Bonuses can range from 10% to 20% of the base salary, depending on the company and industry.

• Additional Remuneration: This includes stock options, profit-sharing, health benefits, and retirement contributions. Tech companies, especially startups, often offer stock options as a significant part of the compensation package to attract talent.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills with the latest tools and technologies in AI/ML and data science. 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 up higher-paying opportunities and leadership roles.

• Networking: Building a strong professional network can lead to new job opportunities and salary negotiations. Attend industry conferences, join professional organizations, and participate in online forums.

• Leadership Roles: Aim for roles with more responsibility, such as team lead or project manager, which typically come with higher pay.

Educational Requirements

Most Data Modeler positions require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master's degree or higher, especially for more advanced roles. Coursework in data structures, algorithms, database management, and machine learning is highly beneficial.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise:

• Certified Data Management Professional (CDMP): This certification is recognized globally and covers a wide range of data management skills.

• Microsoft Certified: Azure Data Scientist Associate: Useful if you are working with Microsoft's Azure platform.

• AWS Certified Machine Learning – Specialty: Beneficial for those working with Amazon Web Services.

• Google Professional Data Engineer: Ideal for those using Google Cloud Platform.

Experience Requirements

Typically, employers look for candidates with 3-5 years of experience in data modeling, data analysis, or a related field. Experience with specific tools and technologies such as SQL, Python, R, and data visualization tools is often required. Experience in a particular industry, such as finance, healthcare, or technology, can also be advantageous.

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