Forecasting Systems

Forecasting Systems Data Jobs

2 jobs found

1d ago

Data Scientist, Demand Forecasting

Amazon.com Services LLC Bellevue, WA

Bellevue, WA

1d ago

$108k - $160k/yr Full time Analytics Data Analysis Data Analytics

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Job Description

An onsite Data Scientist, Demand Forecasting role with Amazon.com Services LLC based in Bellevue, WA. The position offers a salary range of USD 108,300 to 160,000 per year and requires at least a bachelor's degree along with a minimum of one year of relevant experience. The role centers on building large scale foundation models for demand forecasting across hundreds of millions of products, geographies, and business contexts, and it entails designing and conducting experiments, managing end to end forecasting model lifecycles, and translating findings into production impact.

Responsibilities

Design and run scalable experiments to evaluate foundation model performance across hundreds of millions of products, geographies, and business verticals.
Lead the end to end lifecycle of forecasting models from research and experimentation through production deployment, including defining success metrics, obtaining stakeholder sign off, and guiding rollout.
Run online and offline labs to measure real world impact of forecast improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes.
Develop and deploy production grade deep learning and statistical models using Python, Scala, SQL, and related tools.
Perform large scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development.
Translate complex research findings into clear insights and recommendations for technical and non technical stakeholders at all levels.
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top tier venues.

Requirements

1 or more years of experience with data querying languages such as SQL, scripting languages like Python, or statistical/mathematical software such as R, SAS, or Matlab.
2 or more years as a data or research scientist, statistician, or quantitative analyst in an internet based company with large and complex data sources.
Bachelor's degree.

Technologies

Python
Scala
SQL

Benefits

Health insurance
401(k) matching
Paid time off
Parental leave
Sign on payments
Restricted stock units RSUs

About the Team

The Demand Forecasting team sits at the heart of Amazon's supply chain, building the science that determines what products are available, when, and at what cost for hundreds of millions of customers worldwide. Our mission is to push the frontier of large scale time series forecasting and to deploy science where it creates real, measurable impact. We are a team of scientists who value both research rigor and real world outcomes. We do not publish

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6d ago

Sr Data Scientist, Demand Planning

Intuit San Diego, CA

San Diego, CA

6d ago

$150k - $203k/yr Full time Analytics Big Data Business Intelligence

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Job Description

Intuit offers a benefits-forward culture with a cash bonus, equity rewards, and a comprehensive benefits package. This on-site role is based in San Diego, CA.

Location: San Diego, CA (onsite)

Salary: USD 149,500 - 202,500 per year

Overview

Intuit is seeking a Senior Data Scientist to own demand planning for the Full Service offering within the Consumer Group's Expert Network. You will be the primary modeler and analyst for forecasting Full Service Order volume, translating funnel signals into staffing inputs, and improving forecast accuracy across pre-season, in-season, and off-season horizons. This is an individual-contributor role with high visibility and cross-functional influence on workforce decisions.

What you will do

Lead end-to-end demand forecasting for Full Service, from early-season outlook to real-time in-season adjustments
Develop and maintain models that convert funnel signals (trade-up rates, FSO attach, offer acceptance) into actionable demand inputs for capacity planning
Produce interval-level, daily, and weekly forecasts that inform staffing and partner capacity across internal systems and external channels
Advance forecasting methodology by blending time-series models, regression approaches, and machine learning techniques to improve accuracy
Build scenario models with confidence intervals to quantify risk, including upside and downside demand cases for peak season
Explore and incorporate new signal sources such as marketing spend curves, product funnel data, historical tax filing trends, and macro indicators
Serve as the embedded data science partner for Workforce Management and Capacity Planning, translating outputs into staffing recommendations and operational levers
Collaborate with Finance on demand-to-revenue reconciliation and capacity cost modeling
Work with Marketing and Product on offer strategy and its downstream demand impact, including FSO trade-up promotions and LT offer windows
Support real-time in-season analytics, tracking WIP burndown, FSO funnel conversion, and coverage gap signals
Build and maintain dashboards and data products that surface demand risk to operational and leadership audiences
Contribute to post-season retrospectives on forecast accuracy, bias analysis, and methodology improvements
Write and maintain production-quality SQL and Python code against Intuit's datalake datasets related to capacity planning and FSO funnels
Partner with Data Engineering to improve upstream data quality and pipeline reliability for forecasting use cases
Document models, assumptions, and methodologies to enable reproducibility and stakeholder trust