Applied Machine Learning Scientist Salary in 2022

Salary details

The average Applied Machine Learning Scientist salary lies between USD 75,000 and USD 108,000 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

Top 20 Job Tags for Applied Machine Learning Scientist roles

The three most common job tag items assiciated with Applied Machine Learning Scientist job listings are Python, Machine Learning and PyTorch. 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 | 5 jobs Machine Learning | 5 jobs PyTorch | 5 jobs Deep Learning | 4 jobs TensorFlow | 4 jobs Research | 4 jobs PhD | 4 jobs Engineering | 3 jobs Mathematics | 3 jobs Computer Science | 3 jobs Scikit-learn | 2 jobs Testing | 2 jobs A/B testing | 2 jobs ML models | 2 jobs Statistics | 2 jobs Scala | 1 jobs NLP | 1 jobs Big Data | 1 jobs Keras | 1 jobs Pandas | 1 jobs

Top 20 Job Perks/Benefits for Applied Machine Learning Scientist roles

The three most common job benefits and perks assiciated with Applied Machine Learning Scientist job listings are Career development, Health care and 401(k) matching. 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 | 3 jobs Health care | 2 jobs 401(k) matching | 1 jobs Equity / stock options | 1 jobs Parental leave | 1 jobs Flex hours | 1 jobs Flex vacation | 1 jobs Gear | 1 jobs Competitive pay | 1 jobs Team events | 1 jobs Medical leave | 1 jobs Insurance | 1 jobs Salary bonus | 1 jobs

Salary Composition for an Applied Machine Learning Scientist

The salary for an Applied Machine Learning 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. 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 compensate with bonuses or stock options. Industries such as finance or healthcare may offer higher bonuses due to the critical nature of data-driven decisions. Larger companies often provide more comprehensive benefits packages, including health insurance, retirement plans, and stock options, while startups might offer equity as a significant part of the compensation package.

Steps to Increase Salary from the Current Position

To increase your salary from the current 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 related field can open doors to higher-paying roles.
• Networking: Engage with professional networks and communities. Attending conferences and meetups can lead to new opportunities.
• Leadership Roles: Aim for leadership or managerial positions, which typically offer higher salaries.
• Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if the new company values your specific skill set more.

Educational Requirements for an Applied Machine Learning Scientist

Most positions for an Applied Machine Learning Scientist require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and research. These advanced degrees provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for the role.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your expertise in the field. Some valuable certifications include:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications can help you stand out in the job market and may lead to better job opportunities and salary prospects.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in machine learning or data science roles. Experience with real-world data, model deployment, and working in cross-functional teams is highly valued. Additionally, experience in a specific industry, such as finance, healthcare, or technology, can be advantageous, as it demonstrates your ability to apply machine learning solutions to industry-specific problems.

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