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

Salary details

The average senior-level / expert Statistician salary lies between USD 96,700 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: Nov. 10, 2024

Top 20 Job Tags for Senior-level / Expert Statistician roles

The three most common job tag items assiciated with senior-level / expert Statistician job listings are Statistics, Python and R. 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:

Statistics | 55 jobs Python | 50 jobs R | 47 jobs Research | 47 jobs SAS | 34 jobs Machine Learning | 31 jobs Biostatistics | 31 jobs Data analysis | 30 jobs PhD | 21 jobs SQL | 19 jobs Testing | 19 jobs Mathematics | 19 jobs Data management | 17 jobs Pharma | 17 jobs Bayesian | 13 jobs Economics | 11 jobs Engineering | 10 jobs R&D | 10 jobs Data visualization | 9 jobs Data quality | 9 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Statistician job listings are Career development, Health care and Flex hours. 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 | 36 jobs Health care | 24 jobs Flex hours | 16 jobs Equity / stock options | 14 jobs Flex vacation | 11 jobs Competitive pay | 11 jobs Team events | 9 jobs Startup environment | 8 jobs Insurance | 8 jobs Transparency | 7 jobs Medical leave | 6 jobs Parental leave | 5 jobs Salary bonus | 3 jobs 401(k) matching | 2 jobs Wellness | 2 jobs Conferences | 2 jobs Relocation support | 1 jobs Flexible spending account | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Statistician 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 and startups, potentially adding another 5% to 15% to the total compensation. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market.

Increasing Salary

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

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand and can command higher salaries.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Data Science, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or additional degrees can also enhance your qualifications.
• Networking and Industry Engagement: Engage with professional networks, attend conferences, and contribute to industry publications to increase your visibility and open up higher-paying opportunities.

Educational Requirements

For a Senior-level or Expert Statistician role in AI/ML/Data Science, a strong educational background is essential. Most positions require at least a Master's degree in Statistics, Mathematics, Computer Science, or a related field. A Ph.D. is often preferred, especially for roles that involve research or developing new algorithms. The educational focus should be on statistical methods, machine learning, data analysis, and programming.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• TensorFlow Developer Certificate: Demonstrates proficiency in building and deploying machine learning models using TensorFlow.
• AWS Certified Machine Learning – Specialty: Shows expertise in building, training, and deploying machine learning models on the AWS platform.
• Data Science Certifications from Coursera or edX: Courses from reputable institutions can also be beneficial.

Required Experience

Typically, a Senior-level or Expert Statistician in AI/ML/Data Science is expected to have at least 5 to 10 years of relevant experience. This experience should include hands-on work with statistical analysis, machine learning model development, and data manipulation. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued.

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