Do you want to leverage your expertise in machine learning and data science to improve the lives and work of over a million people worldwide?
If so, People eXperience Technology Central Science (PXTCS) would love to discuss how you can make that a reality.
PXTCS is an interdisciplinary team that uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that enhance Amazonians' well-being and their ability to deliver value for Amazon's customers.
We collaborate with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world.
Key job responsibilities
As an Applied Scientist II, you will be responsible for developing and implementing machine learning solutions across our predictive modeling and forecasting work-streams.
You will work on existing models and develop new ones that power leaders across Amazon to make decisions about their businesses.
You will collaborate with scientists and engineers to deliver innovative solutions while working closely with business stakeholders to understand their needs.
A day in the life
You will work across different business domains (corporate, operations, safety) and analysis levels (individual, group, organizational), using various modeling approaches (linear, tree, deep neural network, and LLM-based).
You will develop end-to-end ML solutions from problem formulation to deployment, while maintaining high scientific standards and technical excellence.
BASIC QUALIFICATIONS
- 5+ years of solving business problems through machine learning, data mining and statistical algorithms experience
- PhD, or a Master's degree and experience in CS, CE, ML or related field research
- Strong programming skills in Python and experience with ML frameworks
- Experience with machine learning algorithms and statistical analysis
- Strong analytical and problem-solving skills
- Excellent verbal and written communication skills
PREFERRED QUALIFICATIONS
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Have publications at top-tier peer-reviewed conferences or journals
- Experience in predictive modeling, forecasting, and causal inference
- Experience with cloud computing platforms (AWS preferred)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.