Statistician Salary in United States during 2024

Salary details

The average Statistician salary lies between USD 73,000 and USD 130,920 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 Statistician roles

The three most common job tag items assiciated with Statistician job listings are Statistics, R and Python. 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 | 141 jobs R | 125 jobs Python | 122 jobs Research | 113 jobs SAS | 70 jobs Biostatistics | 68 jobs Machine Learning | 67 jobs Data analysis | 66 jobs Mathematics | 58 jobs PhD | 48 jobs SQL | 42 jobs Testing | 35 jobs Data management | 35 jobs Pharma | 34 jobs Engineering | 28 jobs Consulting | 28 jobs Economics | 25 jobs Bayesian | 25 jobs Excel | 22 jobs R&D | 20 jobs

Top 20 Job Perks/Benefits for Statistician roles

The three most common job benefits and perks assiciated with Statistician job listings are Career development, Health care and Equity / stock options. 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 | 93 jobs Health care | 60 jobs Equity / stock options | 41 jobs Competitive pay | 41 jobs Flex hours | 39 jobs Flex vacation | 23 jobs Startup environment | 22 jobs Team events | 22 jobs Medical leave | 19 jobs Insurance | 19 jobs Salary bonus | 17 jobs Parental leave | 14 jobs Transparency | 13 jobs 401(k) matching | 11 jobs Wellness | 8 jobs Conferences | 8 jobs Relocation support | 6 jobs Flexible spending account | 4 jobs Fitness / gym | 3 jobs Home office stipend | 2 jobs

Salary Composition

In the United States, the salary composition for AI/ML/Data Science roles can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies.

• Region: Salaries tend to be higher in tech hubs like San Francisco, New York, and Seattle due to the higher cost of living and competitive job markets. In these areas, bonuses and stock options are often a significant part of the compensation package.
• Industry: Tech companies, finance, and healthcare often offer higher salaries compared to academia or government roles. In finance, bonuses can be substantial, sometimes equaling or exceeding the base salary.
• Company Size: Larger companies may offer more comprehensive benefits and stock options, while startups might offer lower base salaries but higher equity stakes.

Increasing Salary

To increase your salary from a median of USD 115,460, consider the following strategies:

• Specialize: Develop expertise in a niche area of AI/ML, such as natural language processing, computer vision, or reinforcement learning. Specialists often command higher salaries.
• Leadership Roles: Transition into managerial or leadership positions, such as a team lead or project manager, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Attending workshops, conferences, and pursuing further education can make you more valuable.
• Networking: Build a strong professional network. Engaging with industry professionals can lead to opportunities with higher pay.

Educational Requirements

Most AI/ML/Data Science roles require at least a bachelor's degree in a related field such as statistics, computer science, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for research-intensive positions. Advanced degrees can provide a deeper understanding of complex algorithms and data analysis techniques, making candidates more competitive.

Helpful Certifications

While not always required, certain certifications can enhance your credentials and demonstrate your expertise:

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in data science or a related field. Experience with data analysis, statistical modeling, and machine learning algorithms is crucial. Practical experience with programming languages such as Python or R, and familiarity with data manipulation tools like SQL, is often required.

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