Applied Data Scientist Salary in 2022

Salary details

The average Applied Data Scientist salary lies between USD 50,000 and USD 177,000 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: Dec. 22, 2024

Salary trend

Top 20 Job Tags for Applied Data Scientist roles

The three most common job tag items assiciated with Applied Data Scientist job listings are Python, Machine Learning and Engineering. 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 | 34 jobs Machine Learning | 34 jobs Engineering | 34 jobs Statistics | 31 jobs R | 28 jobs SQL | 28 jobs Research | 25 jobs Finance | 22 jobs Economics | 21 jobs Consulting | 21 jobs Causal inference | 21 jobs Data Analytics | 19 jobs Data management | 19 jobs Statistical modeling | 18 jobs Mathematics | 13 jobs Tableau | 9 jobs ML models | 9 jobs Physics | 7 jobs Computer Science | 6 jobs Deep Learning | 5 jobs

Top 20 Job Perks/Benefits for Applied Data Scientist roles

The three most common job benefits and perks assiciated with Applied Data Scientist job listings are Career development, Flex hours and Competitive pay. 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 | 31 jobs Flex hours | 27 jobs Competitive pay | 27 jobs Health care | 24 jobs 401(k) matching | 23 jobs Flex vacation | 23 jobs Parental leave | 22 jobs Startup environment | 22 jobs Wellness | 21 jobs Insurance | 21 jobs Unlimited paid time off | 21 jobs Team events | 7 jobs Home office stipend | 5 jobs Salary bonus | 2 jobs Equity / stock options | 1 jobs Conferences | 1 jobs Medical leave | 1 jobs

Salary Composition

The salary for an Applied Data Scientist can vary significantly based on factors such as region, industry, and company size. Typically, the compensation package is composed of a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. In regions like Silicon Valley, the base salary might be higher due to the cost of living, while bonuses and stock options can form a substantial part of the total compensation. In contrast, companies in other regions might offer a lower base salary but compensate with higher bonuses or benefits. Industries such as finance or tech tend to offer more competitive packages compared to academia or non-profits. Larger companies often provide more comprehensive benefits and stock options, whereas smaller startups might offer equity as a significant part of the package to attract talent.

Increasing Salary

To increase your salary from the position of an Applied Data Scientist, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Advanced Education: Pursuing further education, such as a master's or Ph.D., can open doors to higher-paying roles.
• Leadership Roles: Transitioning into leadership or managerial roles can significantly boost your salary.
• Industry Switch: Moving to a higher-paying industry, such as finance or tech, can result in a salary increase.
• Networking: Building a strong professional network can lead to opportunities in higher-paying positions.

Educational Requirements

Most Applied Data Scientist roles require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for more advanced positions. These programs provide a strong foundation in data analysis, machine learning, and statistical modeling, which are crucial for the role.

Helpful Certifications

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

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

These certifications can validate your skills and knowledge, making you a more attractive candidate 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, machine learning models, and programming languages like Python or R is crucial. Additionally, experience in handling large datasets and using data visualization tools is often required. For senior roles, more extensive experience, including project management and leadership, is expected.

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