Salary for Senior-level / Expert Analyst during 2024

Salary details

The average senior-level / expert Analyst salary lies between USD 87,728 and USD 150,000 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. 10, 2024

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

The three most common job tag items assiciated with senior-level / expert Analyst job listings are SQL, Python and Statistics. 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 | 5079 jobs Python | 4168 jobs Statistics | 3439 jobs Tableau | 3099 jobs Data analysis | 2848 jobs Engineering | 2823 jobs Excel | 2411 jobs Power BI | 2209 jobs R | 2152 jobs Research | 1910 jobs Data Analytics | 1910 jobs Computer Science | 1898 jobs Finance | 1836 jobs Data visualization | 1779 jobs Testing | 1772 jobs Mathematics | 1768 jobs Business Intelligence | 1533 jobs Data quality | 1491 jobs Machine Learning | 1453 jobs Economics | 1217 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Analyst 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 | 4267 jobs Health care | 2903 jobs Flex hours | 1903 jobs Competitive pay | 1824 jobs Equity / stock options | 1583 jobs Startup environment | 1484 jobs Team events | 1379 jobs Insurance | 1376 jobs Flex vacation | 1242 jobs Medical leave | 1152 jobs Salary bonus | 1125 jobs Parental leave | 1088 jobs Wellness | 910 jobs 401(k) matching | 747 jobs Transparency | 354 jobs Fitness / gym | 279 jobs Home office stipend | 237 jobs Gear | 196 jobs Unlimited paid time off | 191 jobs Relocation support | 189 jobs

Salary Composition

The salary for a Senior-level or Expert Analyst in AI/ML/Data Science typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part 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 and stock options can be substantial, often making up a significant portion of the total compensation. In contrast, in regions with a lower cost of living, the base salary might be more dominant. Larger companies or those in high-growth industries may offer more competitive bonuses and stock options compared to smaller firms or those in more traditional sectors.

Increasing Salary

To increase your salary from a Senior-level position, consider pursuing leadership roles such as a team lead or managerial position. Developing expertise in a niche area of AI/ML, such as natural language processing or computer vision, can also make you more valuable. Networking within the industry and attending conferences can open up opportunities for higher-paying roles. Additionally, contributing to open-source projects or publishing research can enhance your reputation and lead to better job offers. Negotiating your salary based on market research and your contributions to the company can also be effective.

Educational Requirements

Most Senior-level positions in AI/ML/Data Science require at least a master's degree in a related field such as computer science, data science, statistics, or mathematics. A Ph.D. can be advantageous, especially for roles that involve research or developing new algorithms. Employers often look for candidates with a strong foundation in programming, data analysis, and machine learning principles. Relevant coursework or projects that demonstrate your ability to apply theoretical knowledge to practical problems can also be beneficial.

Helpful Certificates

While not always mandatory, certain certifications can enhance your credentials and demonstrate your commitment to professional development. Certifications such as the Certified Data Scientist (CDS), TensorFlow Developer Certificate, or AWS Certified Machine Learning – Specialty can be valuable. These certifications show that you have a recognized level of expertise and are familiar with industry-standard tools and practices. Additionally, completing online courses from platforms like Coursera, edX, or Udacity can provide certificates that bolster your resume.

Required Experience

Typically, a Senior-level position requires at least 5-10 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. Experience leading projects or teams is often expected, as is a proven track record of solving complex problems and delivering results. Familiarity with industry-specific applications of AI/ML can also be advantageous, as it demonstrates your ability to apply your skills in a business context.

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