Salary for Executive-level / Director Analyst during 2024

Salary details

The average executive-level / director Analyst salary lies between USD 109,120 and USD 170,760 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 Executive-level / Director Analyst roles

The three most common job tag items assiciated with executive-level / director Analyst job listings are Python, SQL 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:

Python | 83 jobs SQL | 76 jobs Statistics | 74 jobs Research | 62 jobs Finance | 60 jobs Excel | 51 jobs Data analysis | 51 jobs Testing | 50 jobs Engineering | 46 jobs Data Analytics | 46 jobs Mathematics | 44 jobs Tableau | 41 jobs Data quality | 35 jobs Banking | 34 jobs Computer Science | 34 jobs Credit risk | 31 jobs R | 29 jobs Machine Learning | 29 jobs Data management | 26 jobs Architecture | 24 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Analyst roles

The three most common job benefits and perks assiciated with executive-level / director Analyst job listings are Career development, Health care and Competitive pay. 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 | 99 jobs Health care | 70 jobs Competitive pay | 68 jobs Wellness | 32 jobs Insurance | 32 jobs Medical leave | 31 jobs Startup environment | 29 jobs Flex hours | 27 jobs Equity / stock options | 21 jobs Parental leave | 19 jobs Salary bonus | 19 jobs Transparency | 14 jobs Team events | 13 jobs 401(k) matching | 9 jobs Flex vacation | 9 jobs Conferences | 9 jobs Unlimited paid time off | 9 jobs Travel | 3 jobs Relocation support | 3 jobs Gear | 1 jobs

Salary Composition

The salary for an Executive-level or Director Analyst role in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly based on region, industry, and company size.

• Region: In the United States, for instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more substantial equity packages compared to other regions. In Europe, cities like London or Berlin might offer competitive salaries but with different bonus structures.

• Industry: In the finance or healthcare sectors, bonuses might be more performance-driven, reflecting the company's financial success or project outcomes. In contrast, tech companies might offer more in terms of stock options.

• Company Size: Larger companies often provide more structured bonus programs and comprehensive benefits, while startups might offer lower base salaries but compensate with significant equity stakes.

Increasing Salary Potential

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and methodologies. Specializing in niche areas like deep learning, natural language processing, or AI ethics can make you more valuable.

• Leadership Development: Enhance your leadership and management skills. Pursuing executive education programs or leadership certifications can prepare you for higher roles.

• Networking: Build a strong professional network within the industry. Engaging with industry leaders and participating in conferences can open up opportunities for higher-paying roles.

• Performance and Results: Demonstrate your ability to drive significant business outcomes through AI/ML initiatives. Documenting and showcasing successful projects can position you for salary negotiations or promotions.

Educational Requirements

Most executive-level roles in AI/ML/Data Science require at least a master's degree in a relevant field such as computer science, data science, statistics, or engineering. A Ph.D. can be advantageous, especially for roles that require deep technical expertise or research capabilities. Business acumen is also crucial, so an MBA or courses in business management can be beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and expertise:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.

• AWS Certified Machine Learning – Specialty: Demonstrates your expertise in building, training, and deploying machine learning models on AWS.

• Google Professional Machine Learning Engineer: Certifies your ability to design, build, and productionize ML models.

• Data Science Council of America (DASCA) Certifications: Offers various levels of data science certifications that can be useful.

Experience Requirements

Typically, these roles require extensive experience, often 10+ years, in data science, machine learning, or related fields. Experience should include:

• Leading AI/ML projects and teams.
• Proven track record of implementing data-driven strategies.
• Experience in strategic decision-making and influencing business outcomes.
• Familiarity with industry-specific applications of AI/ML.

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