Description

Are you a data enthusiast? Do the world's most complex data and analytics systems and advancements in generative AI and LLMs inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision-making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! We are looking for a motivated individual with strong analytical and communication skills to join the effort in advancing our work in PXT from the data and analytics capabilities we have today to what will be essential tomorrow.

This magnificent challenge is a terrific opportunity to analyze Amazon’s data and generate actionable recommendations using optimization and simulation. Come build with us!

In this role, your main focus will be to perform analysis, synthesize information, identify business opportunities, provide project direction, and communicate business and technical requirements within the team and across stakeholder groups. You will consider the day-to-day needs of our continuously evolving analytics world and insist on the standards required to build automated and scalable solutions for tomorrow. You will assist in defining trade-offs and quantifying opportunities for a variety of projects. You will learn current processes, build metrics, educate diverse stakeholder groups, assist in initial solution design, and audit all model implementations. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made.

The ideal candidate will have a strong ability to model real-world data with high complexity and deliver high-quality analysis, data products, and optimization models for strategic decisions. They are excited to be part of, and learn from, a large tech and non-tech team, ready to dig into the details to find insights that direct decisions. The successful candidate will have good communication skills and an ability to speak at a level appropriate for the audience, and will collaborate effectively with scientists, product managers, and business stakeholders.

Key job responsibilities

• Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models.

• Discover causal relationships in our data and recommend independent variables to be used in predictive and prescriptive analyses.

• Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering).

• Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management.

• Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area.

• Innovate by adapting new modeling techniques and procedures. Process large scale datasets using distributed computing platform to build models, mining insights from data and prototyping models that optimize towards various business goals and metrics.

• Passionate about working with huge data sets (training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets.

• Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.

• Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers.

• Interact with cross-functional teams and make business recommendations i.e., cost-benefit, forecasting, experiment analysis and present findings to leadership team.

About the team

Amazon Stores People Experience Technology (PXT) Analytics Team owns and creates the necessary data modeling to facilitate reporting and analytics, acquire new data sources, and build comprehensive data visualizations across the employment lifecycle, including promotions, retention, and transfers within the Amazon Stores Organization. The team owns the provision of Descriptive, Diagnostic, Predictive, and Prescriptive Analytics for the PXT Talent Management (TM) organization and beyond. Carrying the leaders, employees, and customers through the different transformational stages of data analytics, reporting and program implementation to drive deep learnings, process improvements, and strategic recommendations through employee data.

Basic Qualifications

• Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.

• 3+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience.

• 3+ years of data querying languages (e.g., SQL, Hadoop/Hive) experience.

• 3+ years of data visualization using AWS QuickSight and similar tools.

• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.

• Experience applying theoretical models in an applied environment.

Preferred Qualifications

• Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue).

• Working knowledge of generative AI and hands on experience in deploying and hosting Large Foundational Models.

• Experience managing data pipelines.

• Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent) and statistical models.

• Experience working with data engineers and business intelligence engineers collaboratively.

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 $143,300/year in our lowest geographic market up to $247,600/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.