Data Scientist II, Long Term Planning and Forecasting

Amazon; Seattle (WA); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Medical, Dental, and Vision Coverage

Maternity and Parental Leave Options

Paid Time Off (PTO)

401(k) Plan

Job summary

Amazon is looking for an experienced Data Scientist II to drive scientific tooling that supports business customer interactions with forecasts and plans. This role involves developing models and frameworks to enhance decision-making across teams. The ideal candidate will have a Master's degree in a STEM field and experience with data querying languages, machine learning, and statistical modeling. Working knowledge of programming languages like Python and a collaborative approach are essential. The position offers benefits, including medical coverage and paid time off.

Qualifications

• 2+ years of data scientist experience.
• 3+ years of experience with data querying languages (e.g., SQL).
• 3+ years of experience with machine learning/statistical modeling tools.
• 1+ years of guiding a group of researchers.
• 1+ years of working with evaluating AI systems.

Responsibilities

• Develop causal inference models and automated explainability frameworks.
• Enable leadership to understand forecast and actual divergence.
• Build automated variance decomposition models.
• Maintain a causal model library with hypothesis generation pipelines.
• Develop GenAI-powered narrative generation capabilities.

Skills

Data querying languages (SQL)

Scripting languages (Python)

Machine learning/statistical modeling

Causal inference

Time-series econometrics

Education

Master's degree in STEM

Tools

R

SAS

MATLAB

Job description

Data Scientist II, Long Term Planning and Forecasting

Job ID: 10414903 | Amazon.com Services LLC

We are seeking an experienced Data Scientist to drive scientific tooling supporting how Amazon’s business customers interact with LTPF forecasts and plans. As a science leader within the LTPF, you will be responsible for building the multi‑year roadmap for customer engagement, ensuring business stakeholders across Amazon can seamlessly access, understand, and act upon our forecasting outputs. You will manage the lifecycle of complex, cross‑functional programs that transform how Operations, Stores, and Finance teams leverage LTPF insights for strategic decision‑making.

Key Responsibilities

• Develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF’s forecasts and plans into actionable business intelligence.
• Enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
• Build automated Plan‑vs‑Actual and Actual‑vs‑Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics.
• Build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time‑series econometrics, and Bayesian methods.
• Develop GenAI‑powered narrative generation capabilities that synthesize quantitative variance outputs into human‑readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.

Basic Qualifications

• 2+ years of data scientist experience.
• 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python) or statistical/mathematical software (e.g., R, SAS, MATLAB).
• 3+ years of experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance.
• 1+ years of guiding and coaching a group of researchers.
• 1+ years of working with or evaluating AI systems.
• 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content.
• Master’s degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in STEM.
• Experience applying theoretical models in an applied environment.

Preferred Qualifications

• 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 defining and creating benchmarks for assessing GenAI model performance.
• Experience effectively communicating complex concepts through written and verbal communication.

Benefits

• Medical, Dental, and Vision Coverage.
• Maternity and Parental Leave Options.
• Paid Time Off (PTO).
• 401(k) Plan.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.