Salary for Mid-level / Intermediate Data Scientist during 2024

Salary details

The average mid-level / intermediate Data Scientist salary lies between USD 98,300 and USD 177,190 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, Statistics and Machine Learning. 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:

Python | 2742 jobs Statistics | 2402 jobs Machine Learning | 2356 jobs SQL | 2112 jobs Engineering | 1885 jobs Computer Science | 1619 jobs R | 1608 jobs Mathematics | 1456 jobs Research | 1306 jobs Data analysis | 1089 jobs ML models | 930 jobs AWS | 800 jobs Testing | 780 jobs Data visualization | 732 jobs Tableau | 684 jobs Pipelines | 676 jobs Spark | 631 jobs NLP | 626 jobs Big Data | 585 jobs Security | 575 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 2024 and the number of open jobs that where offering them during that period:

Career development | 2226 jobs Health care | 1186 jobs Flex hours | 780 jobs Equity / stock options | 777 jobs Competitive pay | 599 jobs Insurance | 556 jobs Startup environment | 551 jobs Medical leave | 541 jobs Parental leave | 501 jobs Team events | 466 jobs Salary bonus | 459 jobs Flex vacation | 449 jobs 401(k) matching | 356 jobs Wellness | 316 jobs Conferences | 137 jobs Flexible spending account | 123 jobs Unlimited paid time off | 122 jobs Relocation support | 103 jobs Transparency | 101 jobs Fitness / gym | 95 jobs

Salary Composition

The salary for a mid-level or intermediate data scientist typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The composition can vary significantly based on region, industry, and company size:

• Region: In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living, with bonuses and stock options forming a significant part of the total compensation. In contrast, regions with a lower cost of living might offer a lower base salary but could compensate with other benefits.

• Industry: Industries such as finance and technology often offer higher salaries and bonuses compared to sectors like healthcare or education. The demand for data-driven decision-making in these industries drives up compensation packages.

• Company Size: Larger companies may offer more comprehensive benefits and stock options, while startups might provide equity as a significant part of the compensation package 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 in emerging technologies such as deep learning, natural language processing, or cloud computing. Specializing in a niche area can make you more valuable.

• 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 increase your earning potential.

• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.

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 provide a competitive edge. Some roles may also value interdisciplinary studies that combine technical skills with business acumen.

Helpful Certifications

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

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

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

Required Experience

Typically, a mid-level data scientist is expected to have 3-5 years of experience in data science or a related field. This experience should include hands-on work with data analysis, machine learning models, and data visualization tools. Experience in a specific industry can also be beneficial, as it demonstrates domain knowledge.

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