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

Salary details

The average senior-level / expert Data Specialist salary lies between USD 83,960 and USD 142,000 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: Dec. 22, 2024

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Data Specialist job listings are SQL, Research and Data management. 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 | 94 jobs Research | 89 jobs Data management | 85 jobs Data quality | 78 jobs Excel | 77 jobs Data analysis | 76 jobs Engineering | 67 jobs Python | 65 jobs Computer Science | 61 jobs Power BI | 60 jobs Testing | 54 jobs Security | 49 jobs Finance | 46 jobs Privacy | 46 jobs R | 45 jobs Statistics | 45 jobs Tableau | 43 jobs Agile | 36 jobs Banking | 35 jobs Data governance | 35 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Specialist job listings are Career development, Health care and Flex hours. 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 | 133 jobs Health care | 97 jobs Flex hours | 89 jobs Competitive pay | 55 jobs Startup environment | 50 jobs Equity / stock options | 42 jobs Flex vacation | 39 jobs Insurance | 37 jobs Team events | 33 jobs Salary bonus | 24 jobs Medical leave | 23 jobs Parental leave | 19 jobs Wellness | 18 jobs Relocation support | 15 jobs 401(k) matching | 10 jobs Transparency | 9 jobs Home office stipend | 7 jobs Flexible spending account | 7 jobs Gear | 6 jobs Conferences | 5 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Specialist in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based 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%. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can add a significant amount to the total compensation, especially if the company performs well. 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 market.

Increasing Salary

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

• Specialization: Develop expertise in a niche area of AI/ML, such as natural language processing, computer vision, or reinforcement learning, which can make you more valuable to employers.
• 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 by attending workshops, conferences, and online courses.
• Networking: Build a strong professional network by engaging with industry peers, joining relevant professional organizations, and attending industry events.
• 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 Specialist roles require at least a master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. A Ph.D. can be advantageous, especially for roles that involve research or advanced technical challenges. Employers often look for candidates with a strong foundation in quantitative skills, programming, and data analysis.

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 help validate your skills and knowledge in specific tools and platforms commonly used in the industry.

Required Experience

Typically, a Senior-level or Expert Data Specialist 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 experience with relevant programming languages and tools such as Python, R, SQL, TensorFlow, and PyTorch. Experience in leading projects or teams can also be beneficial.

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