Salary for Mid-level / Intermediate Applied Machine Learning Scientist during 2022

Salary details

The average mid-level / intermediate Applied Machine Learning Scientist salary lies between USD 75,000 and USD 97,712 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

Top 20 Job Tags for Mid-level / Intermediate Applied Machine Learning Scientist roles

The three most common job tag items assiciated with mid-level / intermediate Applied Machine Learning Scientist job listings are Python, Deep Learning and Machine Learning. 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 | 2 jobs Deep Learning | 2 jobs Machine Learning | 2 jobs PyTorch | 2 jobs Research | 2 jobs PhD | 2 jobs Statistics | 2 jobs Mathematics | 2 jobs NLP | 1 jobs Big Data | 1 jobs TensorFlow | 1 jobs Pandas | 1 jobs Scikit-learn | 1 jobs Kubernetes | 1 jobs AWS | 1 jobs NumPy | 1 jobs Engineering | 1 jobs Data Analytics | 1 jobs Security | 1 jobs SciPy | 1 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Applied Machine Learning Scientist roles

The three most common job benefits and perks assiciated with mid-level / intermediate Applied Machine Learning Scientist job listings are Career development, Equity / stock options and Parental leave. 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 | 2 jobs Equity / stock options | 1 jobs Parental leave | 1 jobs Flex hours | 1 jobs Flex vacation | 1 jobs Health care | 1 jobs Gear | 1 jobs Competitive pay | 1 jobs Medical leave | 1 jobs Salary bonus | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Applied Machine Learning Scientist typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The composition can vary significantly depending on the region, industry, and company size.

• Region: In tech hubs like Silicon Valley or New York, the base salary might be higher due to the cost of living and competitive job market. In contrast, regions with a lower cost of living might offer a lower base salary but compensate with other benefits.
• Industry: Industries such as finance or healthcare may offer higher bonuses due to the critical nature of data-driven decisions in these fields. Tech companies might provide stock options as part of the compensation package.
• Company Size: Larger companies often have structured bonus programs and additional benefits like health insurance, retirement plans, and professional development funds. Startups might offer equity or stock options as a significant part of the compensation to attract talent.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open up higher-paying opportunities and leadership roles.
• Networking: Engage with professional communities, attend conferences, and participate in workshops to expand your network and learn about new opportunities.
• Performance and Negotiation: Consistently demonstrate your value through successful projects and be prepared to negotiate your salary during performance reviews or when offered a new position.

Educational Requirements

Most mid-level applied machine learning scientist roles require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, a master's degree is often preferred and can be a significant advantage. Some positions may also consider candidates with equivalent practical experience in lieu of formal education.

Helpful Certificates

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

• Certified Machine Learning Professional (CMLP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

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

Required Experience

Typically, a mid-level position requires 3-5 years of experience in machine learning or data science roles. This experience should include hands-on work with machine learning models, data analysis, and familiarity with programming languages such as Python or R. Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn is also essential.

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