The Digital Discovery team is responsible for developing advanced algorithms and modeling techniques to acquire new customers and improve engagement for digital business including eBooks, Music, Audible, and Prime.
In this pivotal role, you will leverage your expertise in machine learning and deep learning to build predictive models aimed at acquiring new customers and driving deeper engagement with existing customers across these digital offerings. This will involve developing propensity models for various digital products, optimizing targeting strategies for different placements, and identifying real-time customer digital interests.
Collaborating closely with the engineering team, you will be responsible for the end-to-end lifecycle of these ML models - from architecture and training to production deployment. Your primary focus will be on uncovering customer pain points and devising novel, data-driven solutions to address them. This will require proposing hypotheses, validating them through offline experimentation, and ultimately running rigorous A/B tests to validate the online performance of your innovations. Throughout this process, you will develop production-ready code that can seamlessly integrate with the systems powering Amazon’s digital businesses. Your work will directly contribute to enhancing the discoverability and engagement of digital products and subscriptions.
If you are a passionate, self-driven individual who thrives in a fast-paced, collaborative environment and is eager to push the boundaries of what’s possible in AI and ML, we encourage you to apply for this exciting opportunity on the Digital Discovery team.
Key job responsibilities
- Convert business problem in digital discovery into a Science problem to improve recommendation.
- Work with Data Engineering and BI teams to identify features and build data pipelines.
- Use and enhance ML Ops tools to train, validate, deploy, and compare the models with automatic retraining.
- Explain model performance to tech and business leaders.
- Work with peer community in Science to present, review and publish the model reports and papers.
- Mentor junior Scientists.
About the team
Amazon Digital Acceleration powers ordering, subscriptions, and device management for Prime, Amazon Video, Music, Audible, Alexa, and Kindle, amongst other digital businesses. We process billions of digital purchases every year and enable our digital businesses to grow their businesses worldwide. We are on a mission to be earth's best provider of one-time and recurring digital commerce, delivering a seamless and enjoyable post-purchase customer experience.
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.
- Proven track record of developing and deploying cutting-edge AI/ML models to solve complex, real-world problems.
- Strong coding skills in Python, familiarity with popular ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), and excellent problem-solving and communication abilities are essential.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.