Salary for Mid-level / Intermediate Data Scientist in United States during 2022

Salary details

The average mid-level / intermediate Data Scientist salary lies between USD 110,000 and USD 155,000 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

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 SQL. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Python | 477 jobs Machine Learning | 451 jobs SQL | 337 jobs Statistics | 317 jobs Engineering | 302 jobs Computer Science | 294 jobs Research | 277 jobs R | 275 jobs Mathematics | 209 jobs NLP | 177 jobs PhD | 134 jobs Data visualization | 131 jobs Data Mining | 128 jobs Tableau | 126 jobs Testing | 124 jobs Big Data | 118 jobs AWS | 116 jobs Classification | 109 jobs Consulting | 108 jobs Spark | 107 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 2022 and the number of open jobs that where offering them during that period:

Career development | 450 jobs Health care | 186 jobs Flex hours | 165 jobs Startup environment | 129 jobs Team events | 113 jobs Equity / stock options | 106 jobs Competitive pay | 101 jobs Conferences | 85 jobs Flex vacation | 75 jobs Salary bonus | 70 jobs Home office stipend | 67 jobs Insurance | 61 jobs Medical leave | 47 jobs Parental leave | 41 jobs 401(k) matching | 37 jobs Wellness | 35 jobs Fitness / gym | 33 jobs Gear | 30 jobs Unlimited paid time off | 23 jobs Lunch / meals | 17 jobs

Salary Composition for Mid-level Data Scientists

The salary for a mid-level data scientist in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the bulk of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. In tech hubs like Silicon Valley, bonuses and stock options can be substantial, often making up a significant portion of the total compensation. In contrast, companies in regions with a lower cost of living or in industries like healthcare or finance might offer smaller bonuses but more comprehensive benefits packages. Larger companies often provide more competitive compensation packages, including higher base salaries and more generous bonuses, compared to smaller startups.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools such as deep learning, natural language processing, or cloud computing. Mastery of advanced machine learning techniques can make you more valuable.
• Specialization: Focus on a niche area within data science, such as computer vision or AI ethics, which can make you stand out and command higher salaries.
• Networking: Attend industry conferences, workshops, and meetups to expand your professional network. Networking can lead to new job opportunities or collaborations that might offer better compensation.
• Advanced Education: Pursuing further education, such as a Ph.D. or an MBA, can open doors to higher-level positions with increased pay.
• Leadership Roles: Aim for roles that involve leading projects or teams, as these often come with higher salaries and additional responsibilities.

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 increasingly common and often preferred by employers. Advanced degrees provide a deeper understanding of complex data science concepts and methodologies, which can be crucial for tackling more challenging projects.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

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

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

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, machine learning model development, and data visualization. Experience in handling real-world data problems and delivering actionable insights is crucial. Additionally, familiarity with programming languages like Python or R, and tools such as TensorFlow, PyTorch, or SQL, is often required.

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