Sr. Data Scientist (Forecasting)
Agentic Ai
Ai Agent
Ai Agent Platform
Analytics
Artificial Intelligence
Artificial Intelligence Engineer
Business Analytics
Business Intelligence
Data
Data Analysis
Data Analytics
Data Analytics Tools
Data Engineer
Data Pipeline
Data Platform
Data Processing
Data Science
Data Science Ml
Data Visualization
Data Warehouse
Database
Databases
Demand Forecasting
DevOps
Digital Marketing
Financial Planning
Forecasting
Generative AI
Hr Technology
Machine Learning
Machine Learning Engineering
Microsoft
Ml Ops
Power BI
Reporting and Analytics
SQL
Job Description
Nestlé IT & Digital Americas is looking for a Sr. Data Scientist (Forecasting) to support Nestlé USA Digital through production-grade forecasting work. You will partner closely with Supply Chain Planning and Analytics teams to design and deploy statistical and machine learning models, while bringing Agentic AI and GenAI capabilities into forecasting workflows that improve accuracy and decision-making.
This onsite role is based in Arlington, VA and focuses on scalable forecasting processes, KPI monitoring, and enablement across cross-functional stakeholders.
What you’ll do
- Design, develop, test, and deploy statistical and machine learning forecasting models in production on cloud-based analytics platforms, emphasizing demand pattern recognition, algorithm selection, outlier correction, and parameter optimization to reduce bias and improve forecast accuracy.
- Build and maintain structured, programmatic forecasting pipelines that run at scale, using ML Ops practices to automate weekly forecast generation and reduce manual effort.
- Embed Agentic AI and GenAI into forecasting workflows to identify opportunities to improve accuracy, automate root cause analysis, and support insights generation and decision-making.
- Continuously evaluate and apply emerging AI/ML methods, including deep learning and probabilistic forecasting, to increase accuracy and scalability across a complex portfolio of SKUs, clusters, and data sources.
- Act as a liaison between technical and functional teams by partnering with Supply Chain Planning leads and collaborating with stakeholders across Marketing, Finance, and Sales to connect business needs with system and process solutions.
- Contribute to Enterprise Forecasting as part of the One Planning initiative and support Customer Order Fulfilment improvements with standardized, scalable, cross-functional forecasting solutions.
- Deliver training and forecast office hours to Supply Chain Planning users to build analytics literacy, increase adoption, and strengthen enterprise value.
- Create and enhance Power BI reports for forecast KPI monitoring and data validation, and present findings using data visualization and PowerPoint tailored to the audience.
Requirements
- Bachelor’s degree in statistics, mathematics, economics, business, or a related field.
- 5+ years of experience in data science, forecasting, or advanced analytics, including hands-on experience with SQL, Python, or a similar language.
- 5+ years extracting, transforming, and analyzing large datasets, plus experience creating data visualizations to communicate insights.
- 3+ years deploying and maintaining machine learning models in production, including regression, classification, time series modeling, and feature engineering.
Tools and technologies
- SQL, Python, Machine learning, Power BI, PowerPoint
- ML Ops, Databricks, Snowflake, Microsoft Azure
- GenAI, Agentic AI, deep learning, probabilistic forecasting
Compensation and benefits
- Salary: USD 110,000 - 160,000 per year
- 401k with company match
- Healthcare coverage
- Performance-based incentives
- Competitive total rewards package
Additional preferences
- Master’s degree in statistics, mathematics, economics, business, or a related discipline is preferred.
- Preferred experience with ML Ops practices, cloud and AI/ML platforms (Databricks, Snowflake, Microsoft Azure), GenAI solutions, and Microsoft Power BI.
- Preferred experience supporting enterprise-scale transformation or Supply Chain planning initiatives in an Agile environment.