Data Scientist, AppStore Quality Tech

Data Scientist, AppStore Quality Tech

Description

Appstore Quality tech team builds tools, using AI and engineering techniques to provide the best quality apps to Amazon Appstore users. We are a team of highly-motivated, engaged, and responsive professionals who enable the core testing and quality infrastructure of Amazon Appstore. Come join our team and be a part of history as we deliver results for our customers.

Appstore Quality team's mission is to automate all types of functional, non functional, and compliance checks on apps submitted by appstore app developers to enable north star vision of publishing apps in under 5 hours.

Our team uses various ML/AI/Generative AI techniques to automatically detect violations in images and text metadata submitted by developers. We are working on ambitious project AI projects such as building LLM, auto navigate a mobile app to detect inside app issues and violations.

We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment.

This role involves working closely with Sr Data Scientist, Principal engineer, and engineering team to build ML and AL based solutions in meeting our north start vision.

Key job responsibilities
• Implement statistical methods to solve specific business problems utilizing code (Python, Scala, etc.).
• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
• Collaborate with program management, product management, software developers, data engineering, and business leaders to provide science support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models.
• Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance.
• Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations.
• Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology
• Excellent prompt engineering skillset with a deep knowledge of LLMs, embeddings, transformer models.
• Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers




About the team
In Appstore, “We entertain, and delight, hundreds of millions of people across devices with a vast selection of relevant apps, games, and services by making it trivially easy for developers to deliver”. Appstore team enables the customer and developer flywheel on devices by enabling developers to seamlessly launch and manage their apps/ in-app content on Amazon. It helps customers discover, buy and engage with these apps on Fire TV, Fire Tablets and mobile devices. The technologies we build on vary from device software, to high scale services, to efficient tools for developers.

Basic Qualifications

- 4+ years of data scientist experience
- 4+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience applying theoretical models in an applied environment

Preferred Qualifications

- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree