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

Salary details

The average senior-level / expert Data Developer salary lies between USD 98,500 and USD 180,000 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

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

The three most common job tag items assiciated with senior-level / expert Data Developer job listings are SQL, Python and Pipelines. 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 | 146 jobs Python | 115 jobs Pipelines | 111 jobs Engineering | 103 jobs ETL | 90 jobs Spark | 83 jobs AWS | 74 jobs Azure | 74 jobs Data pipelines | 65 jobs Architecture | 63 jobs Data quality | 62 jobs Big Data | 58 jobs Security | 51 jobs Data warehouse | 49 jobs Agile | 48 jobs Databricks | 48 jobs CI/CD | 48 jobs Research | 47 jobs Testing | 45 jobs Computer Science | 43 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Developer job listings are Career development, Health care and Fitness / gym. 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 | 107 jobs Health care | 67 jobs Fitness / gym | 64 jobs Flex hours | 37 jobs Parental leave | 27 jobs Competitive pay | 24 jobs Equity / stock options | 21 jobs Team events | 21 jobs Startup environment | 19 jobs Flex vacation | 16 jobs Wellness | 14 jobs Insurance | 12 jobs Transparency | 11 jobs Medical leave | 7 jobs Relocation support | 6 jobs Salary bonus | 6 jobs Home office stipend | 5 jobs Conferences | 3 jobs Lunch / meals | 2 jobs Travel | 2 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Developer in AI/ML/Data Science typically includes a combination of a fixed base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly, often comprising 10% to 20% of the total compensation, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, is more common in larger tech companies and startups, potentially making up 5% to 15% of the total package. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets. Industry-wise, tech companies and financial services often offer higher compensation compared to academia or non-profit sectors.

Increasing Salary Further

To increase your salary beyond the median of USD 133,500, 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 job offers or performance reviews.

Educational Requirements

Most Senior-level or Expert Data Developer roles in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Data Science, Statistics, or Mathematics. However, a master's degree or Ph.D. is often preferred, especially for roles involving complex problem-solving and research. Advanced degrees provide a deeper understanding of theoretical concepts and practical applications, which are crucial for high-level positions.

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)
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

These certifications can validate your skills in specific tools and platforms, making you a more attractive candidate.

Required Experience

Typically, a Senior-level or Expert Data Developer position requires at least 5 to 10 years of experience in data science, machine learning, or a related field. This experience should include hands-on work with data analysis, model development, and deployment, as well as a proven track record of successful projects. Experience in leading teams or projects is also highly valued, as it demonstrates your ability to manage complex tasks and collaborate effectively.

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