Salary for Senior-level / Expert Data Strategist in United States during 2024

Salary details

The average senior-level / expert Data Strategist salary lies between USD 110,100 and USD 185,000 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: Nov. 17, 2024

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Data Strategist job listings are Data strategy, Security and Architecture. 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:

Data strategy | 32 jobs Security | 17 jobs Architecture | 17 jobs Data management | 17 jobs Consulting | 16 jobs Research | 13 jobs Data governance | 13 jobs Engineering | 12 jobs Computer Science | 12 jobs Python | 11 jobs Statistics | 11 jobs Privacy | 11 jobs Machine Learning | 10 jobs Tableau | 10 jobs SQL | 10 jobs Data Analytics | 10 jobs Data analysis | 10 jobs Data visualization | 9 jobs Data quality | 9 jobs R | 8 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Strategist job listings are Career development, Health care and Parental leave. 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 | 34 jobs Health care | 15 jobs Parental leave | 12 jobs Team events | 10 jobs Salary bonus | 9 jobs 401(k) matching | 7 jobs Equity / stock options | 7 jobs Flex hours | 7 jobs Wellness | 6 jobs Competitive pay | 6 jobs Startup environment | 5 jobs Insurance | 5 jobs Conferences | 4 jobs Medical leave | 3 jobs Home office stipend | 3 jobs Unlimited paid time off | 3 jobs Flex vacation | 1 jobs Gear | 1 jobs Fitness / gym | 1 jobs Relocation support | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Strategist 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 70% to 85%. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can add a significant amount to the total compensation, especially if the company performs well.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco, New York, or Seattle tend to be higher due to the cost of living and competitive job markets. Industry-wise, tech companies, finance, and healthcare often offer higher compensation packages compared to academia or non-profit sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and bonuses.

Increasing Salary

To increase your salary further from a Senior-level Data Strategist position, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML, such as natural language processing, computer vision, or reinforcement learning, which can make you more valuable to employers.
• Leadership Roles: Transition into leadership or managerial roles, such as Head of Data Science or Chief Data Officer, which typically come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or courses can enhance your skill set and marketability.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during job offers or performance reviews.

Educational Requirements

Most Senior-level Data Strategist positions require at least a master's degree in a relevant field such as Data Science, Computer Science, Statistics, or Mathematics. A Ph.D. can be advantageous, especially for roles that involve research or advanced technical work. Additionally, a strong foundation in business or management can be beneficial, as these roles often require strategic thinking and the ability to align data initiatives with business goals.

Helpful Certifications

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

• Certified Data Scientist (CDS)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• SAS Certified Data Scientist

These certifications can validate your skills in specific tools and platforms, making you more competitive in the job market.

Required Experience

Typically, a Senior-level Data Strategist role requires at least 5-10 years of experience in data science, analytics, or a related field. This experience should include a proven track record of leading data-driven projects, developing and implementing data strategies, and working with cross-functional teams. Experience in a specific industry can also be beneficial, as it provides domain knowledge that can be crucial for strategic decision-making.

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