Salary for Senior-level / Expert Principal Statistical Programmer in United States during 2024

Salary details

The average senior-level / expert Principal Statistical Programmer salary lies between USD 106,200 and USD 218,000 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. 22, 2024

Top 20 Job Tags for Senior-level / Expert Principal Statistical Programmer roles

The three most common job tag items assiciated with senior-level / expert Principal Statistical Programmer job listings are Statistics, SAS and Research. 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 | 80 jobs SAS | 67 jobs Research | 51 jobs Pharma | 47 jobs CDISC | 45 jobs Computer Science | 42 jobs Mathematics | 38 jobs Biostatistics | 32 jobs Data management | 31 jobs R | 30 jobs Data analysis | 28 jobs XML | 24 jobs GCP | 16 jobs SQL | 13 jobs Consulting | 12 jobs Classification | 12 jobs Engineering | 11 jobs R&D | 10 jobs RDBMS | 9 jobs Testing | 6 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Principal Statistical Programmer roles

The three most common job benefits and perks assiciated with senior-level / expert Principal Statistical Programmer job listings are Career development, Health care and Startup environment. 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 | 43 jobs Health care | 30 jobs Startup environment | 24 jobs Team events | 16 jobs Equity / stock options | 9 jobs Parental leave | 9 jobs Flex hours | 9 jobs Wellness | 9 jobs Competitive pay | 9 jobs Medical leave | 6 jobs Insurance | 6 jobs Flex vacation | 3 jobs Travel | 3 jobs Gear | 3 jobs Fitness / gym | 3 jobs Conferences | 2 jobs 401(k) matching | 1 jobs Transparency | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Principal Statistical Programmer in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In tech hubs like Silicon Valley or New York City, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: Performance-based bonuses are common and can vary widely. They are often tied to individual performance, team success, or company profitability. In larger tech companies, bonuses can be a significant part of the total compensation.

• Additional Remuneration: This includes stock options, restricted stock units (RSUs), and other benefits like health insurance, retirement plans, and paid time off. Startups might offer more equity as part of the package, while established companies might provide more comprehensive benefits.

Increasing Salary Further

To increase your salary beyond the median of USD 151,800, consider the following strategies:

• Specialize Further: Developing expertise in a niche area of AI/ML, such as deep learning, natural language processing, or computer vision, can make you more valuable.

• Leadership Roles: Transitioning into leadership or managerial roles can lead to higher compensation. This might involve leading a team of data scientists or overseeing large-scale projects.

• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Attending workshops, conferences, and pursuing advanced certifications can enhance your skill set.

• Networking: Building a strong professional network can open up opportunities for higher-paying positions. Engage with industry groups, attend meetups, and connect with peers on platforms like LinkedIn.

Educational Requirements

For a Senior-level or Expert Principal Statistical Programmer, a strong educational background is essential. Most positions require at least a master's degree in a relevant field such as:

• Computer Science
• Statistics
• Mathematics
• Data Science
• Engineering

A Ph.D. can be advantageous, especially for roles that involve research or developing new algorithms.

Helpful Certifications

While not always mandatory, certain certifications can bolster your credentials and demonstrate your expertise:

• Certified Analytics Professional (CAP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills and make you stand out in a competitive job market.

Required Experience

Typically, a Senior-level or Expert Principal Statistical Programmer is expected to have:

• 8-10 years of experience in data science, statistical programming, or a related field.
• Proven track record of working on complex projects and delivering results.
• Experience with programming languages such as Python, R, or SAS.
• Familiarity with machine learning frameworks and tools.

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