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

Salary details

The average senior-level / expert Data Analytics Lead salary lies between USD 128,300 and USD 195,500 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. 22, 2024

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

The three most common job tag items assiciated with senior-level / expert Data Analytics Lead job listings are Data Analytics, SQL and Python. 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 Analytics | 120 jobs SQL | 72 jobs Python | 71 jobs Statistics | 54 jobs Engineering | 51 jobs Power BI | 47 jobs Tableau | 44 jobs Data analysis | 40 jobs Machine Learning | 35 jobs Privacy | 35 jobs Security | 32 jobs Computer Science | 32 jobs Agile | 31 jobs Data visualization | 31 jobs Data quality | 31 jobs Research | 30 jobs Business Intelligence | 29 jobs Data management | 29 jobs R | 28 jobs Excel | 28 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Analytics Lead 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 | 83 jobs Health care | 48 jobs Competitive pay | 38 jobs Startup environment | 34 jobs Medical leave | 33 jobs Flex hours | 29 jobs Parental leave | 25 jobs Equity / stock options | 24 jobs Insurance | 24 jobs Salary bonus | 23 jobs Wellness | 19 jobs Team events | 19 jobs Flex vacation | 13 jobs 401(k) matching | 10 jobs Transparency | 10 jobs Relocation support | 9 jobs Unlimited paid time off | 7 jobs Home office stipend | 5 jobs Conferences | 4 jobs Fertility benefits | 4 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Analytics Lead typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10% to 20%. Additional remuneration, such as stock options, profit sharing, or other incentives, can make up the remaining 5% to 10%.

The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more substantial equity packages. In contrast, companies in the Midwest or South might offer lower base salaries but compensate with higher bonuses or other benefits. Larger companies often provide more comprehensive benefits and stock options, while smaller startups might offer more equity to attract top talent.

Increasing Salary Further

To increase your salary beyond the median of USD 166,000, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML or data science, such as deep learning, natural language processing, or AI ethics, which are in high demand and can command higher salaries.
• Leadership and Management Skills: Develop strong leadership and project management skills to move into higher managerial roles, such as Director of Data Science or Chief Data Officer.
• Networking and Industry Engagement: Engage with industry conferences, workshops, and professional networks to increase your visibility and open up opportunities for higher-paying roles.
• Continuous Learning and Certification: Stay updated with the latest technologies and methodologies in AI/ML and data science through continuous learning and obtaining relevant certifications.

Educational Requirements

Most Senior-level or Expert Data Analytics Lead positions require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data modeling and algorithm development. Advanced degrees provide a deeper understanding of theoretical concepts and practical applications, which are crucial for leading data analytics projects.

Helpful Certifications

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

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

These certifications validate your skills in data analytics, machine learning, and cloud-based data solutions, making you a more competitive candidate.

Required Experience

Typically, a Senior-level or Expert Data Analytics Lead role requires at least 7 to 10 years of experience in data analytics, data science, or a related field. This experience should include hands-on work with data analysis, statistical modeling, and machine learning algorithms. Additionally, experience in leading teams, managing projects, and collaborating with cross-functional teams is crucial for this role.

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