Salary for Senior-level / Expert Data Developer during 2024

Salary details

The average senior-level / expert Data Developer salary lies between USD 84,000 and USD 137,000 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. 24, 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 | 149 jobs Python | 118 jobs Pipelines | 113 jobs Engineering | 103 jobs ETL | 91 jobs Spark | 85 jobs Azure | 75 jobs AWS | 74 jobs Data pipelines | 65 jobs Architecture | 63 jobs Data quality | 62 jobs Big Data | 59 jobs Security | 51 jobs Databricks | 50 jobs CI/CD | 49 jobs Data warehouse | 49 jobs Agile | 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 | 67 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

The salary composition for a Senior-level or Expert Data Developer in AI/ML/Data Science typically includes a mix of fixed salary, bonuses, and additional remuneration. The fixed salary is the base pay and usually constitutes the largest portion of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses might be more substantial compared to other areas. Additional remuneration can include stock options, profit-sharing, and other incentives, which are more common in larger tech companies or startups. The industry also plays a role; for instance, finance and healthcare sectors might offer higher bonuses compared to academia or non-profits. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and bonuses.

Increasing Salary

To increase your salary further from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML and data science. Specializing in niche areas like deep learning, natural language processing, or AI ethics can make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Data Science, which typically offer higher salaries.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.
• Certifications and Education: Obtain advanced certifications or pursue further education, such as a Ph.D. or an MBA, which can open doors to higher-paying roles.

Educational Requirements

Most senior-level positions 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 that involve complex problem-solving and research. Advanced degrees can provide a deeper understanding of machine learning algorithms, data analysis techniques, and statistical modeling, which are crucial for expert-level positions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility 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 for senior roles.

Required Experience

Typically, a Senior-level Data Developer in AI/ML/Data Science is expected to have at least 5-10 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued. Demonstrated success in solving complex data problems and delivering impactful insights is crucial for advancing to expert-level positions.

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