Bear Robotics Salary in 2024

Salary details

The average Bear Robotics salary lies between USD 88,000 and USD 205,000 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. 15, 2024

Top 20 Job Tags for Bear Robotics roles

The three most common job tag items assiciated with Bear Robotics job listings are Robotics, Python and Engineering. 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:

Robotics | 12 jobs Python | 9 jobs Engineering | 7 jobs Linux | 6 jobs Computer Science | 5 jobs Machine Learning | 4 jobs Tableau | 4 jobs Security | 4 jobs Git | 4 jobs Looker | 3 jobs Testing | 3 jobs GCP | 3 jobs Pipelines | 3 jobs SLAM | 2 jobs OpenCV | 2 jobs SQL | 2 jobs Power BI | 2 jobs Architecture | 2 jobs Data visualization | 2 jobs Terraform | 2 jobs

Top 20 Job Perks/Benefits for Bear Robotics roles

The three most common job benefits and perks assiciated with Bear Robotics job listings are Career development, Flex hours and Team events. 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 | 4 jobs Flex hours | 2 jobs Team events | 2 jobs 401(k) matching | 1 jobs Lunch / meals | 1 jobs Equity / stock options | 1 jobs Parental leave | 1 jobs Flex vacation | 1 jobs Wellness | 1 jobs Health care | 1 jobs Startup environment | 1 jobs Medical leave | 1 jobs Insurance | 1 jobs Salary bonus | 1 jobs Flexible spending account | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

In the AI/ML/Data Science field, the salary composition can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In tech hubs like Silicon Valley, the base salary might be higher compared to other regions due to the cost of living and competitive market.

• Bonuses: These are performance-based and can vary widely. In larger companies or high-growth startups, bonuses can be substantial, often tied to individual performance, team success, or company profitability.

• Additional Remuneration: This includes stock options, equity, or other benefits like health insurance, retirement plans, and professional development funds. Startups might offer more equity as part of the compensation package, while established companies might provide more comprehensive benefits.

Increasing Salary

To increase your salary from a position in AI/ML/Data Science, consider the following strategies:

• Skill Enhancement: Continuously update your skills with the latest technologies and methodologies in AI/ML. Specializing in high-demand 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 up higher-paying opportunities, especially in research-intensive roles.

• Networking: Building a strong professional network can lead to new opportunities and insights into higher-paying roles. Attend industry conferences, join professional groups, and engage in online communities.

• Leadership Roles: Aim for leadership or managerial positions, which typically offer higher salaries. This might involve developing soft skills like communication, project management, and team leadership.

Educational Requirements

Most positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master's degree or Ph.D., especially for more advanced roles. A strong foundation in mathematics, statistics, and programming is essential.

Helpful Certificates

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

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

These certifications can validate your skills and knowledge, making you a more competitive candidate.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in data science or a related field. Experience with specific tools and technologies, such as Python, R, SQL, TensorFlow, or PyTorch, is often required. Practical experience in handling real-world data, building models, and deploying machine learning solutions is highly valued.

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