Salary for Mid-level / Intermediate Data Scientist in United States during 2023

Salary details

The average mid-level / intermediate Data Scientist salary lies between USD 105,000 and USD 170,500 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

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Scientist roles

The three most common job tag items assiciated with mid-level / intermediate Data Scientist job listings are Python, Machine Learning and Statistics. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Python | 599 jobs Machine Learning | 539 jobs Statistics | 464 jobs SQL | 410 jobs Engineering | 372 jobs Computer Science | 325 jobs R | 314 jobs Research | 297 jobs Mathematics | 251 jobs Data analysis | 191 jobs ML models | 179 jobs Testing | 144 jobs Data visualization | 144 jobs AWS | 143 jobs Tableau | 131 jobs Data Mining | 131 jobs NLP | 129 jobs Deep Learning | 124 jobs TensorFlow | 120 jobs Scikit-learn | 116 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Scientist roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Scientist 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 2023 and the number of open jobs that where offering them during that period:

Career development | 524 jobs Health care | 249 jobs Flex hours | 176 jobs Competitive pay | 168 jobs Startup environment | 165 jobs Team events | 150 jobs Equity / stock options | 110 jobs Flex vacation | 110 jobs Parental leave | 103 jobs Insurance | 99 jobs Salary bonus | 83 jobs Medical leave | 81 jobs Conferences | 73 jobs 401(k) matching | 61 jobs Fitness / gym | 48 jobs Wellness | 39 jobs Unlimited paid time off | 37 jobs Home office stipend | 30 jobs Gear | 26 jobs Yoga | 23 jobs

Salary Composition

The salary for a mid-level or intermediate data scientist in the United States typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-85% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually make up 10-20% of the total salary. Additional remuneration might include stock options, especially in tech companies, and other benefits like health insurance, retirement contributions, and paid time off. The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like San Francisco or New York may offer higher base salaries and stock options, while smaller companies might offer more in bonuses to attract talent.

Increasing Salary

To increase your salary from a mid-level data scientist position, consider the following strategies:

• Skill Enhancement: Continuously update your skills, especially in emerging technologies and tools like deep learning, natural language processing, or cloud computing.
• Advanced Education: Pursuing a master's or Ph.D. in data science or a related field can open doors to higher-paying roles.
• Leadership Roles: Transitioning into a managerial or lead data scientist role can significantly boost your salary.
• Industry Shift: Some industries, such as finance or healthcare, may offer higher salaries for data scientists due to the complexity and impact of the work.
• Networking and Visibility: Attend conferences, publish papers, or contribute to open-source projects to increase your visibility and attract better job offers.

Educational Requirements

Most mid-level data scientist positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, a master's degree is often preferred and can be a significant advantage. Some roles may also require specific coursework or experience in machine learning, data mining, or big data technologies.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

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

These certifications can validate your skills and make you more competitive in the job market.

Experience Requirements

Typically, a mid-level data scientist is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data analysis, statistical modeling, and machine learning. Experience with data visualization tools, programming languages like Python or R, and familiarity with databases and big data technologies are also commonly required.

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