Salary for Mid-level / Intermediate Data Scientist during 2022

Salary details

The average mid-level / intermediate Data Scientist salary lies between USD 64,090 and USD 130,000 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: 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 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

The salary composition for a mid-level or intermediate data scientist can vary significantly based on factors such as region, industry, and company size. Generally, the salary is composed of a fixed base salary, a performance-based bonus, and additional remuneration such as stock options or benefits. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, regions with a lower cost of living might offer a smaller base salary but could compensate with a more substantial bonus or stock options. Industries like finance or healthcare may offer higher bonuses due to the critical nature of data-driven decisions in these fields. Larger companies often provide more comprehensive benefits packages, including health insurance, retirement plans, and professional development opportunities, which can add significant value to the overall compensation package.

Increasing 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 these areas can make you more valuable to employers.
• Advanced Education: Pursuing a master's degree or a Ph.D. in data science, computer science, or a related field can open doors to higher-paying roles.
• Networking: Engage with professional networks and communities. Attending conferences, meetups, and workshops can lead to new opportunities and insights into higher-paying roles.
• Leadership Roles: Aim for roles that involve leading projects or teams, as these often come with higher compensation.
• Industry Shift: Consider moving to industries known for higher pay scales, such as finance, tech, or consulting.

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, many employers prefer candidates with a master's degree or higher due to the complex nature of the work. A strong foundation in statistical analysis, machine learning, and programming is essential, and coursework in data visualization and big data technologies can be advantageous.

Helpful Certifications

While not always mandatory, certain certifications can enhance your resume and demonstrate your commitment to the field. Some valuable certifications include:

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

These certifications can validate your skills and knowledge, making you a more attractive candidate for higher-level positions.

Required Experience

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 managing projects or collaborating with cross-functional teams can also be beneficial. Employers look for candidates who have demonstrated the ability to apply data science techniques to solve real-world problems effectively.

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