Salary for Executive-level / Director Analyst in United States during 2024

Salary details

The average executive-level / director Analyst salary lies between USD 113,840 and USD 175,000 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. 15, 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 | 96 jobs SQL | 88 jobs Statistics | 83 jobs Research | 76 jobs Finance | 74 jobs Excel | 64 jobs Testing | 63 jobs Data analysis | 61 jobs Engineering | 55 jobs Tableau | 51 jobs Mathematics | 51 jobs Data Analytics | 50 jobs Data quality | 47 jobs Banking | 44 jobs Computer Science | 37 jobs Credit risk | 35 jobs R | 33 jobs Data management | 33 jobs Machine Learning | 32 jobs Agile | 29 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 | 117 jobs Health care | 85 jobs Competitive pay | 82 jobs Wellness | 40 jobs Medical leave | 37 jobs Insurance | 37 jobs Startup environment | 35 jobs Flex hours | 34 jobs Equity / stock options | 21 jobs Parental leave | 21 jobs Salary bonus | 20 jobs Transparency | 19 jobs Team events | 17 jobs Flex vacation | 11 jobs Conferences | 11 jobs 401(k) matching | 9 jobs Unlimited paid time off | 9 jobs Travel | 3 jobs Relocation support | 3 jobs Gear | 1 jobs

Salary Composition

In the United States, the salary composition for an Executive-level or Director Analyst role 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 60% to 80%. Bonuses can vary significantly depending on the company's performance and individual achievements, usually accounting for 10% to 20% of the total compensation. Additional remuneration, such as stock options, can make up the remaining 10% to 20%, particularly in larger tech firms or startups. The composition can vary by region, with tech hubs like Silicon Valley offering higher equity components, while industries such as finance might offer more substantial cash bonuses. Company size also plays a role, with larger companies typically providing more structured bonus and equity packages.

Increasing Salary Potential

To increase your salary from an Executive-level or Director Analyst position, consider pursuing further specialization in emerging AI/ML technologies or industry-specific applications. Networking within industry circles and attending conferences can open doors to higher-paying opportunities. Additionally, taking on more strategic roles that influence company direction or expanding your responsibilities to include cross-departmental leadership can justify a salary increase. Pursuing an MBA or executive education programs can also enhance your leadership skills and make you a more attractive candidate for higher-paying roles. Negotiating your compensation package by leveraging offers from other companies can also be an effective strategy.

Educational Requirements

Most Executive-level or Director Analyst positions 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 valued, so degrees that combine technical and business education, such as a Master of Business Analytics, can be particularly beneficial. Continuous learning through online courses and workshops is also important to keep up with the rapidly evolving field.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your commitment to the field. Certifications such as the Certified Analytics Professional (CAP), TensorFlow Developer Certificate, or AWS Certified Machine Learning can be beneficial. For those in leadership roles, certifications in project management, such as PMP or Agile, can also be valuable. These certifications can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.

Experience Requirements

Typically, a minimum of 10 to 15 years of experience in data science, machine learning, or a related field is required for an Executive-level or Director Analyst role. This experience should include a mix of technical expertise, project management, and leadership roles. Experience in managing teams, developing and implementing AI/ML strategies, and a proven track record of successful projects are crucial. Industry-specific experience can also be a significant advantage, as it demonstrates your ability to apply AI/ML solutions to real-world business problems.

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