Salary for Mid-level / Intermediate Data Developer in United States during 2024

Salary details

The average mid-level / intermediate Data Developer salary lies between USD 85,000 and USD 145,000 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. 24, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Developer roles

The three most common job tag items assiciated with mid-level / intermediate Data Developer job listings are SQL, ETL and Python. 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 | 77 jobs ETL | 64 jobs Python | 60 jobs Engineering | 50 jobs Big Data | 48 jobs Spark | 44 jobs Pipelines | 41 jobs AWS | 38 jobs Azure | 36 jobs Computer Science | 30 jobs Architecture | 29 jobs Hadoop | 28 jobs Git | 27 jobs Databricks | 27 jobs Agile | 26 jobs Research | 24 jobs Data pipelines | 23 jobs Testing | 23 jobs Data quality | 21 jobs CI/CD | 20 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Developer roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 52 jobs Health care | 38 jobs Fitness / gym | 26 jobs Flex hours | 24 jobs Competitive pay | 12 jobs Parental leave | 10 jobs Equity / stock options | 9 jobs Flex vacation | 6 jobs Startup environment | 6 jobs Team events | 6 jobs Medical leave | 6 jobs Insurance | 6 jobs Salary bonus | 6 jobs Wellness | 4 jobs Gear | 2 jobs Unlimited paid time off | 2 jobs 401(k) matching | 1 jobs Travel | 1 jobs Transparency | 1 jobs Snacks / Drinks | 1 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Data Developer in AI/ML/Data Science typically includes a base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. The base salary often constitutes the majority of the total compensation package, usually ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the total compensation. Additional remuneration, such as stock options, is more common in tech companies and startups, especially in regions like Silicon Valley. In larger corporations or financial institutions, bonuses might be more substantial, reflecting the company's profitability and individual performance.

Steps to Increase Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud computing, and big data technologies.
• Advanced Education: Pursuing a master's degree or specialized certifications can make you more competitive.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends.
• Leadership Roles: Seek opportunities to lead projects or teams, which can demonstrate your capability for higher-level positions.
• Industry Transition: Consider moving to industries with higher pay scales, such as finance or tech, if you are not already in one.

Educational Requirements

Most mid-level 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. A master's degree can be advantageous and is often preferred by employers, especially for roles that require more specialized knowledge or leadership responsibilities. Some positions may also value interdisciplinary degrees that combine technical skills with business acumen.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise in specific areas. Some valuable certifications include:

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

These certifications can help validate your skills and make you stand out in a competitive job market.

Required Experience

Typically, a mid-level data developer role requires 3 to 5 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. Experience with programming languages such as Python or R, as well as familiarity with data manipulation tools and machine learning frameworks, is often expected.

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