Machine Learning at Amazon: Inside the Applied Scientist Role (Salary, Job Market, Skills)

Summary

In this video, an applied scientist at Amazon (specifically Twitch) discusses their role, which bridges machine learning research with practical business applications. The job involves designing algorithms for fraud detection, recommendations, and forecasting, and combines data science, machine learning engineering, and research. The speaker shares insights on daily tasks, the importance of SQL skills, and the high compensation ($250,000-$400,000 per year). The role offers autonomy, intellectual challenges, continuous learning, and real-world impact, making it an ideal career for those passionate about machine learning and technology.

Takeaways

• 😀 Applied scientists at Amazon work at the intersection of machine learning research and practical applications, developing solutions for real-world business challenges.
• 😀 The role involves designing and deploying machine learning algorithms for tasks like fraud detection, recommendations, and forecasting.
• 😀 Applied scientists blend the skills of data scientists, machine learning engineers, and researchers, with a focus on creating real-world impact.
• 😀 A typical day for an applied scientist includes a mix of data science, production system building, and deep work, with limited meetings.
• 😀 SQL skills are crucial for applied scientists, as they regularly write complex queries to extract and analyze data from warehouses.
• 😀 Independence and autonomy are key benefits of the role, with a focus on solving new and diverse challenges without micromanagement.
• 😀 Intellectual challenges and continuous learning are constant in the role, which keeps the work engaging and provides opportunities for innovation.
• 😀 The compensation for applied scientists at Amazon ranges between $250,000 and $400,000 per year, with bonuses and stock options.
• 😀 The demand for applied scientists is expected to grow as AI continues to transform industries, and the role is less likely to be automated.
• 😀 A master's or PhD in a relevant field is typical for this role, but practical experience, projects, and continual learning are equally important for success.
• 😀 The role may not be suitable for those who prefer routine, clearly defined problems or those who want to focus exclusively on coding or theory.

Q & A

What is the role of an applied scientist at Amazon?

An applied scientist at Amazon bridges research and practical application by developing machine learning solutions for real-world business challenges, such as fraud detection, recommendations, and forecasting. They design and implement machine learning algorithms, conduct hands-on research, deploy models to production, and collaborate with teams to align technical solutions with business goals.

How does the role of an applied scientist differ from other roles like data scientists or machine learning engineers?

While there is overlap, the role of an applied scientist sits at the intersection of data science, machine learning engineering, and research. Applied scientists combine analytical rigor, engineering skills, and innovative mindsets but with a focus on practical impact. They bridge the gap between cutting-edge research and production systems, unlike data scientists who focus on generating insights or machine learning engineers who specialize in building systems at scale.

Can you give an example of how the role of an applied scientist at Twitch evolved over time?

When the speaker joined Twitch, the team was primarily focused on analytics, and there was no machine learning infrastructure in place. Their first major project involved building this foundation, setting up AWS tools like SageMaker, Airflow, and alerting systems. Over time, the role expanded to include content understanding, forecasting, fraud detection, and working with the recommendations team.

What does a typical day for an applied scientist look like?

A typical day is highly varied. Some days are spent deep in data science tasks like working in notebooks, analyzing data, and developing new approaches. Other days focus on building production systems, writing code that runs in live environments, and setting up monitoring. Additionally, applied scientists spend time learning, reading technical books, taking courses, and staying updated with industry trends.

How important is SQL in the role of an applied scientist?

SQL is extremely important for an applied scientist. A significant amount of data lives in data warehouses, so applied scientists spend several hours each week writing complex SQL queries. SQL skills are considered as essential as understanding deep learning architectures, especially in environments where data manipulation is key.

What are the key benefits of working as an applied scientist at Twitch or Amazon?

Key benefits include the independence to focus on deep work, intellectual challenge from constantly solving new problems, and opportunities for continual learning. There's also a flexible work environment that promotes work-life balance and autonomy in project selection. Additionally, the compensation is high, and the role provides tangible impact on products used by millions.

What is the typical salary range for an applied scientist at Amazon?

Applied scientists at Amazon typically earn between $250,000 and $400,000 or more per year, which includes base salary, stock options, and bonuses. Compensation at other major tech companies is comparable, though startups may offer lower cash compensation but with higher equity potential.

What kind of educational background is required to become an applied scientist?

The traditional path involves a master's or PhD in fields like computer science, machine learning, or statistics. However, practical experience and the ability to demonstrate skills through projects are just as important, and many successful applied scientists come from non-traditional backgrounds.

What skills are essential for an applied scientist at Amazon?

Key skills include strong production-level coding abilities (particularly in Python), experience with machine learning tools like PyTorch and TensorFlow, knowledge of data science fundamentals such as model evaluation and experiment design, and the ability to translate business problems into technical solutions. SQL skills are also crucial.

What personality traits are well-suited for the role of an applied scientist?

The ideal candidate is self-motivated, enjoys navigating ambiguity, thrives with autonomy, and has a passion for learning. They should be comfortable working on both coding and mathematical aspects of machine learning, enjoy problem-solving, and have a desire to make a tangible impact on products used by millions of people.