Principal Statistical Programmer Salary in 2024

Salary details

The average Principal Statistical Programmer salary lies between USD 106,200 and USD 218,000 globally. 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.

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

Top 20 Job Tags for Principal Statistical Programmer roles

The three most common job tag items assiciated with 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 | 76 jobs SAS | 66 jobs Research | 48 jobs Pharma | 48 jobs CDISC | 47 jobs Computer Science | 40 jobs Mathematics | 35 jobs R | 28 jobs Biostatistics | 27 jobs Data management | 26 jobs XML | 22 jobs Data analysis | 22 jobs GCP | 14 jobs SQL | 13 jobs Engineering | 13 jobs Consulting | 12 jobs RDBMS | 10 jobs Testing | 7 jobs Classification | 7 jobs KPIs | 6 jobs

Top 20 Job Perks/Benefits for Principal Statistical Programmer roles

The three most common job benefits and perks assiciated with 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 | 41 jobs Health care | 33 jobs Startup environment | 23 jobs Flex hours | 12 jobs Team events | 11 jobs Equity / stock options | 10 jobs Parental leave | 9 jobs Wellness | 9 jobs Competitive pay | 9 jobs Insurance | 9 jobs Flex vacation | 6 jobs Medical leave | 6 jobs Travel | 3 jobs Gear | 3 jobs Fitness / gym | 3 jobs Transparency | 3 jobs Salary bonus | 3 jobs 401(k) matching | 2 jobs Conferences | 2 jobs Relocation support | 2 jobs

Salary Composition

The salary for a Principal Statistical Programmer in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual achievements, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can make up the remaining 5-10%.

Regional differences play a significant role in salary composition. For instance, positions in tech hubs like Silicon Valley or New York City may offer higher base salaries and stock options due to the high cost of living and competitive job market. Industry also influences salary composition; tech companies might offer more in stock options, while pharmaceutical companies might provide more comprehensive health benefits. Company size can affect bonuses and stock options, with larger companies often having more structured bonus programs and smaller startups offering more equity.

Increasing Salary

To increase your salary from the position of a Principal Statistical Programmer, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and methodologies in AI/ML and data science. Specializing in niche areas like deep learning, natural language processing, or big data analytics can make you more valuable.

• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Data Science or Head of AI, which typically come with higher compensation.

• Industry Transition: Moving to a higher-paying industry, such as finance or tech, can significantly increase your salary. These industries often value data-driven decision-making and are willing to pay a premium for experienced professionals.

• Networking and Visibility: Increase your professional visibility by speaking at conferences, publishing papers, or contributing to open-source projects. This can lead to opportunities with higher compensation.

Educational Requirements

Most Principal Statistical Programmer roles require at least a master's degree in a relevant field such as statistics, computer science, data science, or a related discipline. A Ph.D. can be advantageous, especially for roles that involve complex problem-solving and research. Advanced degrees demonstrate a deep understanding of statistical methods, programming, and data analysis, which are crucial for this position.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your commitment to professional development:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• SAS Certified Advanced Programmer: Demonstrates proficiency in SAS programming, a common tool in statistical programming.
• TensorFlow Developer Certificate: Shows expertise in using TensorFlow for machine learning and deep learning projects.
• AWS Certified Machine Learning – Specialty: Highlights your ability to design and implement machine learning solutions on AWS.

Required Experience

Typically, a Principal Statistical Programmer is expected to have 8-10 years of experience in statistical programming, data analysis, or a related field. This experience should include a strong track record of working with large datasets, developing statistical models, and using programming languages such as R, Python, or SAS. Experience in leading projects and teams is also highly valued, as this role often involves mentoring junior programmers and collaborating with cross-functional teams.

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