Data Scientist II, AB Ops Analytics
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We are seeking a Data Scientist to join our analytics team. This person will own the design and implementation of scalable and reliable approaches to support or automate decision making throughout the business.
You will do this by analyzing data with a variety of statistical techniques and then building, validating, and implementing models based your analysis. You will not be able to do this alone but by building partnerships across data, engineering, and business teams.
Key job responsibilities
Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult customer or business problems and cases in which the solution approach is unclear.
Proactively seek to identify business opportunities and insights and provide solutions to automate and optimize key internal and external products based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.
Dive deep into the data and other models across the business to identify defects or inefficiencies which materially impact the customer or business, but can be mitigated through corrective actions for the AB Ops use case
Acquire this data by accessing data sources and building the necessary SQL/ETL queries or scripts.
Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies.
Build models and automated tools using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks.
Validate these models against alternative approaches, expected and observed outcome, and other business defined key performance indicators.
Implement these models in a manner which complies with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.
Enable product engineering teams to consume your models through services which can directly power customer-facing experiences.
Inspect the key business metrics/KPIs (even if you did not create them) when your analytics work points to potential gaps or opportunities providing clear, compelling analyses by leveraging your knowledge across the AWS suite of products to support the broader business.
About the team
Amazon Business (AB) launched in the United States in April 2015 with the vision of delivering a comprehensive procurement solution for business customers of all sizes. In the US, AB now serves Fortune 500 companies, hospital systems, local governments, and education organizations. To support AB's mission, the AB Operations team owns end to end customer experience for AB customers right from checkout to final mile delivery and sits under the broader Global Transportation Services (GTS). We are the Single Threaded WW Ops team driving B2B operations, developing products and programs unique to business customers, and enhancing the core Amazon delivery capabilities for commercial addresses. While Amazon has built its core operations over the last two decades mostly catered towards the end-consumer, we recognize that the business customers have unique needs and require a different set of features and services from their e-Commerce provider.
- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Job ID: 152203949
Skills:
Machine Learning, data analysis tools and techniques
Skills:
association rules , Hadoop, SAS, Sql, Decision Trees, Spark, Clustering, Matlab, Python, End-to-End quality test strategy, sampling methods, machine learning and modeling techniques, GIS tools, R, Regression, classifiers, Six Sigma, Quality Management, statistical and experimental design methods
Skills:
Logistic Regression, k-means, Pyspark, Random Forest, Pca, Sql, Tensorflow, Pytorch, XGBoost, Python, AWS, SHAP, scikit-learn, Feature Engineering, GLM, Pricing Models
Skills:
Pyspark, Neural Networks, Tableau, Sql, Random Forest, Deep Learning, Tensorflow, Pytorch, Excel, Python, Generative AI production applications, Model Deployment Frameworks, GLM Regression, Cloud computing tools, Sagemaker, R, Boosting Trees, Kserve, MLFlow
Skills:
Machine Learning, Pyspark, SAS, Scala, Matlab, Python, Sql, Data Analysis, R, Statistical Modeling
