Salary for Executive-level / Director Quantitative Analyst during 2024

Salary details

The average executive-level / director Quantitative Analyst salary lies between USD 95,000 and USD 200,000 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: Dec. 22, 2024

Top 20 Job Tags for Executive-level / Director Quantitative Analyst roles

The three most common job tag items assiciated with executive-level / director Quantitative Analyst job listings are Python, Statistics and Finance. 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 | 23 jobs Statistics | 23 jobs Finance | 16 jobs Credit risk | 16 jobs Mathematics | 16 jobs Engineering | 13 jobs Testing | 13 jobs PhD | 12 jobs ML models | 12 jobs SQL | 11 jobs Research | 11 jobs Computer Science | 11 jobs Physics | 10 jobs R | 9 jobs Machine Learning | 8 jobs Economics | 7 jobs Econometrics | 7 jobs SAS | 6 jobs Data analysis | 6 jobs Probability theory | 5 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Quantitative 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 | 21 jobs Health care | 14 jobs Competitive pay | 11 jobs Medical leave | 7 jobs Insurance | 7 jobs Equity / stock options | 6 jobs Flex hours | 5 jobs Wellness | 4 jobs Salary bonus | 4 jobs Parental leave | 3 jobs 401(k) matching | 1 jobs Home office stipend | 1 jobs Paid sabbatical | 1 jobs

Salary Composition

The salary composition for an Executive-level or Director Quantitative Analyst in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity. The exact composition can vary significantly depending on the region, industry, and company size.

• Base Salary: This is the fixed component and usually constitutes the majority of the total compensation package. In regions like North America and Western Europe, the base salary can be quite substantial, reflecting the high demand for skilled professionals in AI/ML.

• Bonuses: Performance-based bonuses are common and can vary widely. In tech companies or financial institutions, bonuses can be a significant part of the compensation, sometimes ranging from 10% to 50% of the base salary, depending on individual and company performance.

• Additional Remuneration: This may include stock options, equity, or profit-sharing plans, especially in startups or tech companies. Larger companies might offer comprehensive benefits packages, including health insurance, retirement plans, and other perks.

Increasing Salary Further

To increase your salary beyond the median of USD 200,000, 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 and Management: Develop strong leadership and management skills. Taking on more responsibilities, leading larger teams, or managing cross-functional projects can position you for higher-paying roles.

• Networking and Industry Engagement: Engage with industry networks, attend conferences, and publish in reputable journals. Building a strong professional network can open up opportunities for higher-paying positions.

• Negotiation: When offered a new position or during performance reviews, negotiate for higher compensation. Research industry standards and be prepared to justify your request with your achievements and market value.

Educational Requirements

Most executive-level roles in AI/ML/Data Science require advanced degrees. Common educational requirements include:

• Master’s Degree: A Master’s in Data Science, Computer Science, Statistics, or a related field is often required. This provides a strong foundation in quantitative analysis and technical skills.

• Ph.D.: For some high-level positions, especially in research-intensive roles, a Ph.D. may be preferred or required. It demonstrates expertise and the ability to conduct independent research.

Helpful Certificates

While not always mandatory, certain certifications can enhance your profile:

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

• AWS Certified Machine Learning: Useful if you are working with cloud-based AI/ML solutions.

• TensorFlow Developer Certificate: Validates your ability to build and train machine learning models using TensorFlow.

Experience Requirements

Typically, a significant amount of experience is required for executive-level roles:

• 10+ Years in Relevant Fields: Experience in data science, quantitative analysis, or related fields is crucial. This should include a mix of technical and leadership roles.

• Proven Track Record: Demonstrated success in leading projects, managing teams, and delivering results in AI/ML initiatives.

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