below marketmost similar roles pay hereabove market
This role pays less than
63%
of similar roles. Most pay
$140,300–$212,812
— the blue band above.
At the midpoint, this role pays about
$156k
versus about
$177k
for comparable roles.
Based on 240 similar postings.
Employer
About Oracle
Oracle Corporation is a leading multinational technology company specializing in database software, cloud computing, and enterprise software.
Oracle currently has
964 open roles
on FindRole.
Listed pay typically runs
$103,000–$234,600
across 787 roles with salary data.
The Senior Data Scientist - Demand Planning and Forecasting will join the team to develop data-driven forecasting and analytics solutions for networking hardware and data center infrastructure planning. This role involves working with large, complex datasets to identify demand drivers, develop forecasting models, and provide insights for hardware procurement and capacity planning. You will build time-series, statistical, and machine learning models to improve forecast accuracy and stability. Key responsibilities include creating scalable datasets and analytical pipelines, automating recurring reporting processes, and developing reusable frameworks for scenario modeling. The position requires proficiency in Python and advanced SQL to solve technical problems related to data center builds, network capacity, and SKU-level demand. You will collaborate with engineering and supply chain teams to translate business questions into actionable quantitative models.
What does a Data Scientist earn in Washington?
Median $201600 from 31 postings across 15 companies.
Develop and maintain demand forecasting models for networking hardware and data center infrastructure.
Analyze historical demand, deployment trends, and product roadmaps to identify key demand drivers.
Build time-series, statistical, and machine learning models to improve forecast accuracy and stability.
Create analytical models to evaluate base, upside, downside, and what-if scenarios for hardware demand.
Build scalable datasets and analytical pipelines using SQL and Python to support planning workflows.
Develop reusable dashboards and tools to improve visibility into demand trends and planning risks.
Automate recurring analysis, forecasting, reconciliation, and reporting processes.
Communicate analytical findings and practical planning recommendations to engineers and senior leadership.
What we're looking for
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, Operations Research, Economics, or a related quantitative field.
5+ years of experience in data science, applied science, forecasting, demand planning analytics, operations research, or a related quantitative discipline.
Strong hands-on programming experience with Python and advanced SQL.
Experience developing and deploying forecasting or predictive models using real-world business data.
Strong understanding of statistical modeling, time-series forecasting, model evaluation, and experimental or analytical methodologies.
Experience working with large and complex datasets and performing data exploration, feature engineering, modeling, and analysis.
Experience translating business or operational problems into quantitative models and actionable recommendations.
Experience working with planning, supply chain, capacity planning, demand forecasting, or other operational decision-making processes.
Python
SQL
Machine Learning
Generative AI
Large Language Models
LLMs
Statistical Analysis
Predictive Modeling
Causal Inference
AI Agents
Data Science
Experimentation
Model Evaluation
Production Monitoring
Recommendation Systems
Segmentation
Forecasting
Python
SQL
R
Machine Learning
Snowflake
BigQuery
Databricks
Tableau
Power BI
HQL
NoSQL
JSON
XML
Logistic Regression
K-means Clustering
Decision Trees
Support Vector Machines
Data Visualization
Identity Resolution