Applied Scientist III, AWS Central Economics and Science

Amazon; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Join a forward-thinking company as an Applied Scientist, where you'll leverage your expertise in machine learning to create impactful models that drive business strategies. In this dynamic role, you'll collaborate with cross-functional teams to tackle complex challenges and deliver actionable insights. Enjoy a supportive environment that values work-life balance, encourages continuous learning, and fosters innovation. If you're passionate about data and eager to make a difference, this opportunity is perfect for you.

Qualifications

• 3+ years of experience in building machine learning models for business applications.
• Strong programming skills in Java, C++, or Python.

Responsibilities

• Develop and deliver models to guide strategic decision making.
• Collaborate with product, finance, and business teams.

Skills

Machine Learning

Data Analysis

Problem Solving

Communication Skills

Education

PhD in a relevant field

Master's degree with 6+ years of applied research experience

Tools

Java

C++

Python

R

scikit-learn

TensorFlow

Hadoop

Spark

Job description

We are hiring an Applied Scientist for a cross-functional team that builds ML-based products to help AWS sellers understand customers and optimize sales strategies. This scientist will help develop and maintain a suite of ML models that identify the most valuable opportunities and customers for AWS sellers to engage and the types of actions they should take to optimize those engagements.

Key job responsibilities

This applied scientist role partners with AWS business leaders across the organization to develop and deliver models and evidence to guide strategic decision and planning. The successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges and ambiguous starting points, and possesses strong communication skills to effectively interface and collaborate with product, finance, and business teams.

A day in the life

Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It's about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don't encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn't a successful long run strategy. Because we invest in the long run success of our group it's important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement.

About the team

Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn't translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it's not fun, what's the point?

Basic Qualifications

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.