: Applied Science Manager
101 Main Street
Cambridge, MA 02142

Employee Testimonials



The Alexa Feedback organization owns a number of programs and domains which drive high customer engagement and feature discovery, maintains customer trust, understands customers’ feedback, develops new features that provide utility value for customers with special needs, and develops locally relevant experiences. The Alexa Experience Science team applies machine learning and natural language understanding algorithms to improve these programs and the functionality of domains such as News (“Alexa, What's the news?"), Feedback (“Alexa, that was wrong!"), Personality (“Alexa, what’s your favorite color?”), and to advance Alexa’s ability to handle more ambiguous utterances.

We're looking for a Applied Science Manager who combines exceptional technical, research and analytical capabilities to lead a team that will be integral to the continued improvement of Amazon Alexa. You will be responsible for leading a team of research scientists and data experts to build ML models to develop new features, predict key user behaviors and deliver automated decisions, both offline and in real time.

What You Will Do
· Communicating effectively with senior management as well as with colleagues from science, engineering and business backgrounds, in written and verbal forms
· Step in as an experienced member of an applied machine learning research team, establish technical credibility quickly, and help recruit elite machine learning practitioners.
· Contribute to setting up the research vision for the team, and develop and execute on a roadmap that addresses the major questions faced by the domains we serve.
· Raise the bar for research quality and impact. Stay up to date on research results both within and complementary to the Alexa technology space and helping both your team and the larger org utilize tried patterns and state of the art results to work smarter and faster.
· Supporting the career development of your team members.
· Providing technical and scientific guidance to your team members.
· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences


· Master's degree in Research, Computer Science, Applied Mathematics, or a closely related field.
· 5+ years related work experience in areas such as data analytics, data modeling, machine learning, search or personalization-related problems.
· 3+ years of direct people management experience including duties such as performance evaluation and career development.
· Experience in managing and quantifying improvement in multiple business areas resulting from business analytics, optimization techniques, and/or statistical modeling.
· Experience modeling and optimization techniques tailored to meet business needs and proven achievements in production systems.
· Experience as leader of a science team and developing junior members from academia/industry to a business environment.
· Knowledge of various machine learning techniques and key parameters that affect their performance
· Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
· Excellent written and verbal communication skills.


· Ph.D. in Research, Computer Science, Applied Mathematics, or a closely related field.
· Experience with spoken language understanding systems.
· Demonstrated leadership abilities, especially with cross-disciplinary efforts.
· Project management experience.
· Experience with data engineers or business analysts in Big Data analytics.
· A good understanding of analysis of algorithms and computational complexity.
· Expertise in prototyping and scripting languages (e.g. Python) with applications of efficient large-scale data analysis in a complicated system.

Amazon.com is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.


Employee Testimonials

Spyros M.
Senior Principal Scientist, Alexa Machine Learning

“For scientists, this is a great place for doing research because Amazon is very data-driven and metrics-oriented. The rigor expected in scientific publications in terms of running controlled experiments and tracking progress based on well-established metrics is exactly what we see in our team.”

“You also interact with people with strong technical and practical experience and learn from each other,” he says. “You’re exposed to a breadth of challenges, many of them long-term applications for artificial intelligence."

Chao W.
Alexa Science Manager

“Since 2000 I’ve been focused on developing spoken language and machine translation systems that can engage with humans more effectively, and hopefully break down language and other barriers,” Chao says. “We’re still far from systems that truly understand the meaning of what we’re saying, but the progress we’re making with Alexa is incredibly exciting.”

Janet S.
Senior Manager of Applied Modeling and Data Science

“We have much further to go in developing systems that can truly understand and converse with humans naturally.  But I’m incredibly proud of how far we’ve come with Alexa, and super excited about the work teams are doing to make Alexa smarter every day.”

Shankar A.
Senior Manager, Applied Science

“When I first joined the team I didn’t realize just how big and ambitious this initiative really is,” said Shankar. “What’s incredibly exciting for speech scientists like myself is how algorithmic innovations in machine learning and data science have created a sophisticated voiced-based AI like Alexa, and how our work on improving this technology has a positive impact on the day-to-day lives of millions of customers using it."

Chris C.
People Manager

“We have an incredibly diverse, experienced and curious team that is always pushing the envelope even further! Here at Amazon, we pride ourselves on being peculiar. We bring in talent from all around the world, leading to a diversity of background, culture and perspective in each team!” 

Beatriz R.
Team Manager

“I have quickly learned that Amazon is a company where you can actually voice out your ideas and concerns, where you can expect the support and interest of Leadership. We are quick to take action, passionate about improving processes and driven to enhance morale, so being able to speak up without fear has been my best asset. Now at the year mark at ADS, I am happy to say that the culture is one where you are proud to be a member of the team. “