Statistical Programmer Salary in United States during 2024

Salary details

The average Statistical Programmer salary lies between USD 93,500 and USD 175,300 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

Top 20 Job Tags for Statistical Programmer roles

The three most common job tag items assiciated with 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 | 331 jobs SAS | 283 jobs Research | 196 jobs CDISC | 191 jobs Mathematics | 190 jobs Computer Science | 188 jobs Pharma | 148 jobs R | 127 jobs Biostatistics | 110 jobs Data management | 101 jobs Engineering | 77 jobs Data analysis | 76 jobs XML | 70 jobs GCP | 49 jobs Python | 41 jobs Consulting | 38 jobs SQL | 36 jobs R&D | 36 jobs Privacy | 35 jobs PhD | 32 jobs

Top 20 Job Perks/Benefits for Statistical Programmer roles

The three most common job benefits and perks assiciated with Statistical Programmer 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 | 161 jobs Health care | 100 jobs Flex hours | 64 jobs Team events | 63 jobs Competitive pay | 58 jobs Startup environment | 47 jobs Equity / stock options | 40 jobs Insurance | 28 jobs Medical leave | 26 jobs Flex vacation | 21 jobs Salary bonus | 18 jobs Parental leave | 17 jobs Fitness / gym | 15 jobs Wellness | 14 jobs Relocation support | 13 jobs Transparency | 8 jobs Paid sabbatical | 6 jobs Conferences | 5 jobs 401(k) matching | 4 jobs Gear | 4 jobs

Salary Composition

In the United States, the salary composition for a Statistical Programmer in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in tech companies and startups, providing long-term incentives aligned with company growth.

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 markets. Industry-wise, tech and finance sectors often offer higher compensation compared to healthcare or academia. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and bonuses.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to AI/ML, such as deep learning frameworks or big data analytics.
• Advanced Education: Pursuing a master's or Ph.D. in a related field can open doors to higher-level positions and salary brackets.
• Networking: Engage with professional networks and attend industry conferences to increase your visibility and learn about new opportunities.
• Leadership Roles: Aim for leadership or managerial roles within your organization, which typically come with higher pay.
• Industry Transition: Consider moving to a higher-paying industry, such as finance or tech, if you are currently in a lower-paying sector.

Educational Requirements

Most Statistical Programmer roles in AI/ML/Data Science require at least a bachelor's degree in a related field such as statistics, computer science, mathematics, or data science. However, a master's degree is often preferred and can significantly enhance your job prospects and salary potential. Advanced degrees provide a deeper understanding of complex statistical methods and machine learning algorithms, which are crucial for higher-level positions.

Helpful Certifications

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

• 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 analysis.
• TensorFlow Developer Certificate: Shows competence in using TensorFlow for machine learning tasks.
• AWS Certified Machine Learning – Specialty: Highlights your skills in implementing machine learning solutions on the AWS platform.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in statistical programming or a related field. Experience with specific programming languages such as R, Python, or SAS is often required. Additionally, hands-on experience with data manipulation, statistical modeling, and machine learning techniques is crucial. Experience in a particular industry can also be beneficial, as it provides domain-specific knowledge that can be applied to data analysis tasks.

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