Statistical Programmer Salary in 2024

Salary details

The average Statistical Programmer salary lies between USD 85,600 and USD 164,800 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: Dec. 15, 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 | 357 jobs SAS | 303 jobs Research | 215 jobs CDISC | 206 jobs Mathematics | 203 jobs Computer Science | 203 jobs Pharma | 156 jobs R | 139 jobs Biostatistics | 123 jobs Data management | 113 jobs Data analysis | 89 jobs Engineering | 82 jobs XML | 76 jobs GCP | 55 jobs Python | 43 jobs Consulting | 42 jobs R&D | 42 jobs SQL | 40 jobs Privacy | 37 jobs PhD | 34 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 Team events. 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 | 175 jobs Health care | 105 jobs Team events | 71 jobs Flex hours | 67 jobs Competitive pay | 62 jobs Startup environment | 53 jobs Equity / stock options | 45 jobs Insurance | 31 jobs Medical leave | 27 jobs Flex vacation | 23 jobs Salary bonus | 22 jobs Parental leave | 17 jobs Fitness / gym | 16 jobs Wellness | 15 jobs Relocation support | 14 jobs Transparency | 8 jobs Gear | 6 jobs Paid sabbatical | 6 jobs 401(k) matching | 5 jobs Conferences | 5 jobs

Salary Composition

The salary for a 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 the fixed component and usually forms the largest part of the total compensation. Performance bonuses can vary significantly depending on the company's profitability and individual performance metrics. Additional remuneration might include stock options, especially in tech companies, or benefits like health insurance, retirement plans, and paid time off.

• Region: Salaries can vary widely based on geographic location. For instance, positions in tech hubs like Silicon Valley or New York City often offer higher salaries to offset the higher cost of living.
• Industry: Industries such as finance, healthcare, and technology tend to offer higher salaries due to the critical nature of data analysis in these fields.
• Company Size: Larger companies may offer more comprehensive benefits and bonuses, while startups might offer equity as part of the compensation package.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and programming languages. Specializing in high-demand areas like deep learning or natural language processing can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in data science, computer science, or a related field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into roles such as a team lead or project manager can increase your earning potential.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.
• Certifications: Obtaining relevant certifications can demonstrate your expertise and commitment to the field, potentially leading to salary increases.

Educational Requirements

Most positions for Statistical Programmers 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, many employers prefer candidates with a master's degree or higher, especially for more advanced roles. Coursework in machine learning, data analysis, and statistical modeling is highly beneficial.

Helpful Certifications

While not always required, certain certifications can enhance your qualifications and make you more competitive in the job market:

• Certified Analytics Professional (CAP)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• SAS Certified Advanced Programmer for SAS 9

These certifications demonstrate proficiency in specific tools and platforms commonly used in the industry.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in statistical programming or a related field. Experience with data analysis, statistical modeling, and machine learning projects is highly valued. Familiarity with programming languages such as Python, R, and SQL is often required, along with experience using data visualization tools.

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