Decision Scientist, Decision Sciences

Technology, Data & Digital · Data, AI & Analytics · Data Science

In short

Amazon seeks a Decision Scientist I to join the 1P Lending team, applying statistical modeling, machine learning, and experimentation to drive business decisions. The role involves building and validating models, designing A/B tests, analyzing large datasets, and partnering with cross-functional teams to translate insights into actionable strategies.

Responsibilities

Build and validate statistical and machine learning models using standard methodologies (logistic regression, decision trees, random forests, gradient boosting, survival analysis).
Develop classification, regression, and segmentation models to support business decisions.
Monitor deployed models for drift and degradation, and recommend recalibration when needed.
Design, execute, and analyze A/B tests and controlled experiments to evaluate product and policy changes.
Drive end-to-end delivery of scalable data pipelines from ideation to production deployment.
Gather and use large-scale datasets from multiple sources to build analytical solutions.
Write production-quality SQL and Python/R scripts to extract, transform, and analyze data at scale.
Create and maintain metrics and KPIs to quantify model performance and business improvement (e.g., AUC-ROC, precision-recall, Gini, KS statistic).
Partner with product, business, science, and engineering teams to translate complex analyses into actionable recommendations.
Write accurate, clear, and mathematically rigorous technical documents, model documentation, and reports.
Conduct root cause analysis on business performance trends and anomalies.
Deliver artifacts for project components that improve processes or systems to inform business decisions.
Follow best practices to discover and adapt existing knowledge (internal and external research) to meet customer needs.
Understand team ownership, including data pipelines, model infrastructure, and business impact.

Requirements

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), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
Knowledge of machine learning concepts and their application to reasoning and problem-solving.
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience.
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM).

Desired Qualifications

Experience applying quantitative analysis to solve business problems and making data-driven business decisions.
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive).
Experience effectively communicating complex concepts through written and verbal communication.
Experience with AWS Solutions, including EC2, S3, Redshift, EMR (or Hadoop).

Skills

SQLPythonRlogistic regressiongradient boostingsurvival analysisdecision treesrandom forestsclassificationregressionsegmentationSparkHadoopMapReduceHiveEC2S3RedshiftEMR

#Data Science#Machine Learning#Fintech#E-commerce#cloud scale ML infrastructure

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