Sr. Data Scientist, Capacity Planning

Amazon Web Services (AWS); Seattle (WA); On-site; USD 159,200 - 215,300; Full time

Benefits offered by this job

Sign-on payments

Restricted stock units

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services (AWS) is seeking a Data Scientist for its Support Capacity Planning team to model contact and volume forecasting, develop predictive models, and drive operational improvements across data engineering, tooling, workforce management, and finance.

You will work with large-scale processing frameworks like Spark/Hadoop, evaluate models, and deliver data-driven solutions that shape our long-term strategy and cost-saving opportunities.

Qualifications

• 5+ years of experience with data querying languages (SQL), scripting languages (Python), or statistical/mathematical software (R, SAS, MATLAB).
• 4+ years of data science experience.
• Experience with multinomial logistic regression.

Responsibilities

• Establish and execute data management and strategy frameworks, including data collection, storage, integration, and ensuring data quality and integrity.
• Collaborate with cross‑functional teams to identify data‑related challenges and opportunities, develop data‑driven solutions, and align data strategy with organizational objectives.
• Conduct thorough research and analysis to assess data needs and requirements, evaluate existing infrastructure, identify gaps, and propose innovative solutions.
• Leverage large‑scale processing frameworks such as Apache Spark or Hadoop to handle big data and ensure efficient model training and evaluation.
• Continuously evaluate and improve machine learning models by incorporating stakeholder feedback, monitoring real‑world performance, and exploring new algorithms to enhance accuracy and efficiency.
• Develop and implement machine learning models that drive business value, including forecasting future outcomes from historical data, analyzing customer and market trends to craft targeted go‑to‑market strategies, and identifying cost‑saving opportunities through financial analysis.
• Analyze operational data to identify bottlenecks, inefficiencies, and process improvement areas, thereby streamlining operations, reducing costs, and improving customer satisfaction.

Skills

SQL

Python

R

SAS

MATLAB

Multinomial logistic regression

Tools

AWS QuickSight

Tableau

R Shiny

Job description

Description

Do you have proven analytical capabilities to identify business opportunities, develop predictive models, and build optimization algorithms that help us create a state‑of‑the‑art AWS Support organization?

As a Data Scientist on AWS Support’s Capacity Planning team, you will model contact and volume forecasting, uncover insights, and drive business and operational improvements. You will partner with data engineering, tooling, operations, training, workforce management, and finance teams to deliver predictive and optimization solutions that shape our long‑term strategy.

Key Responsibilities

• Establish and execute data management and strategy frameworks, including data collection, storage, integration, and ensuring data quality and integrity.
• Collaborate with cross‑functional teams to identify data‑related challenges and opportunities, develop data‑driven solutions, and align data strategy with organizational objectives.
• Conduct thorough research and analysis to assess data needs and requirements, evaluate existing infrastructure, identify gaps, and propose innovative solutions.
• Leverage large‑scale processing frameworks such as Apache Spark or Hadoop to handle big data and ensure efficient model training and evaluation.
• Continuously evaluate and improve machine learning models by incorporating stakeholder feedback, monitoring real‑world performance, and exploring new algorithms to enhance accuracy and efficiency.
• Develop and implement machine learning models that drive business value, including forecasting future outcomes from historical data, analyzing customer and market trends to craft targeted go‑to‑market strategies, and identifying cost‑saving opportunities through financial analysis.
• Analyze operational data to identify bottlenecks, inefficiencies, and process improvement areas, thereby streamlining operations, reducing costs, and improving customer satisfaction.

Basic Qualifications

• 5+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, MATLAB).
• 4+ years of data science experience.
• Experience with statistical models such as multinomial logistic regression.

Preferred Qualifications

• 2+ years of experience visualizing data with AWS QuickSight, Tableau, R Shiny, or similar tools.
• Experience managing data pipelines.
• Experience as a leader and mentor on a data science team.

Compensation

Base salary range (location dependent):

• USA, Texas (Dallas): $159,200 – $215,300 USD annually
• USA, Washington (Seattle): $159,200 – $215,300 USD annually

Other benefits include sign‑on payments, restricted stock units, health insurance, 401(k) matching, paid time off, and parental leave. For full details, see our benefits page.

Equity

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

We are committed to providing a workplace that accommodates disabilities and renders necessary adjustments during the application and hiring process. For more information, visit https://amazon.jobs/content/en/how-we-hire/accommodations.