Salary for Senior-level / Expert Data Analyst during 2023

Salary details

The average senior-level / expert Data Analyst salary lies between USD 93,000 and USD 144,100 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

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Data Analyst job listings are SQL, Python and Tableau. 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 | 1947 jobs Python | 1386 jobs Tableau | 1187 jobs Statistics | 1121 jobs Data analysis | 950 jobs Engineering | 904 jobs R | 787 jobs Power BI | 756 jobs Excel | 740 jobs Data visualization | 678 jobs Data Analytics | 660 jobs Mathematics | 642 jobs Computer Science | 589 jobs Looker | 563 jobs Finance | 551 jobs Research | 494 jobs Business Intelligence | 494 jobs Machine Learning | 444 jobs KPIs | 443 jobs Testing | 442 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Analyst 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 | 1394 jobs Health care | 872 jobs Startup environment | 663 jobs Flex hours | 653 jobs Equity / stock options | 566 jobs Competitive pay | 536 jobs Flex vacation | 520 jobs Team events | 469 jobs Salary bonus | 437 jobs Insurance | 416 jobs Parental leave | 408 jobs Medical leave | 297 jobs 401(k) matching | 256 jobs Wellness | 227 jobs Home office stipend | 182 jobs Fitness / gym | 169 jobs Gear | 142 jobs Unlimited paid time off | 142 jobs Relocation support | 69 jobs Transparency | 61 jobs

Salary Composition

The salary for a Senior-level or Expert Data Analyst in AI/ML/Data Science typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The fixed base salary is the largest component, often accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 5-10%.

Regional differences play a significant role in salary composition. For instance, tech hubs like San Francisco or New York may offer higher base salaries and stock options due to the high cost of living and competitive job market. Industry also impacts salary composition; tech companies might offer more in stock options, while finance or healthcare sectors might provide higher bonuses. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and smaller startups offering equity as a significant part of the compensation.

Increasing Salary

To increase your salary from a Senior-level Data Analyst 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 big data analytics can make you more valuable.

• Advanced Education: Pursuing further education, such as a master's degree or Ph.D. in data science, computer science, or a related field, can open doors to higher-paying roles.

• Leadership Roles: Transitioning into leadership or managerial roles, such as a Data Science Manager or Director of Analytics, can significantly increase your earning potential.

• Networking and Industry Engagement: Actively participate in industry conferences, workshops, and networking events to increase your visibility and open up opportunities for higher-paying positions.

• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level Data Analyst positions require at least a bachelor's degree in a relevant field such as data science, computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree or higher, especially for expert-level roles. Advanced degrees provide a deeper understanding of complex analytical techniques and theoretical knowledge, which are crucial for tackling sophisticated data challenges.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Microsoft Certified: Azure Data Scientist Associate: Demonstrates proficiency in using Azure's machine learning tools.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems.
• AWS Certified Machine Learning – Specialty: Highlights your skills in building, training, and deploying machine learning models on AWS.

Required Experience

Typically, a Senior-level Data Analyst role requires 5-10 years of experience in data analysis or a related field. This experience should include a proven track record of handling complex data projects, proficiency in data analysis tools and programming languages (such as Python, R, SQL), and experience with machine learning models and techniques. Experience in leading projects or teams can also be beneficial, as it demonstrates your ability to manage and mentor junior analysts.

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