Data Scientist – Decision Support, Analytics and Automation
About The Position
Jack Link’s is building an end-to-end decision support capability that integrates forecasting, measurement, optimization, and scenario planning to power commercial decisions across sales, marketing, finance, and planning. In this hands-on role, you will design, build, and productionize machine learning, optimization, and agentic AI solutions—delivering accurate forecasts, trusted measurement, and practical “what-if” scenarios that drive growth, margin, and efficiency. You will also lead the development and orchestration of AI agents and Retrieval-Augmented Generation (RAG) workflows to automate and augment commercial work. This is a hands-on ML engineering role with strong business partnership and technical leadership responsibilities, supported by a collaborative team of product owners, developers, data engineers, and architects.
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, or related field.
- 5 + years of full-time, professional experience in data science, analytics, or similar.
- Demonstrates a deep interest and strong understanding of consumer behavior and decision-making, including behavioral economics principles, purchasing dynamics, and responses to marketing stimuli, to inform data-driven solutions and business applications
- Possesses strong training in statistics and data science, enabling discernment in identifying, evaluating, and selecting the most appropriate methodological approaches for complex analytical and forecasting challenges.
- Hands on experience working with enterprise, consumer, and market performance data.
- Proficiency in Python for data science and automation.
- Strong understanding of forecasting models, scenario planning, and optimization techniques.
- Hands on experience with 2 or more scenario planning techniques: Monte Carlo Simulation, Digital Twin Modeling, Sensitivity Analysis, What-Ifs, and Optimization Algorithms.
- Familiarity with CI/CD pipelines, model monitoring, and governance frameworks.
- Excellent communication skills to translate analytics into actionable insights.
Nice To Haves
- Master’s degree in Data Science, Analytics, or quantitative related field.
- Experience working in CPG, Retail and E-Comm, Media and Entertainment, Tech platform (Meta, TikTok etc.) or at a specialized commercial analytics/measurement firm.
- Hands-on experience with Azure Machine Learning, Azure DevOps, and Microsoft Fabric.
- Experience deploying AI agents or intelligent automation solutions in enterprise environments.
- Experience with data engineering principles, including ETL, data quality, and integration.
- Familiarity with Microsoft Power BI or other visualization tools for reporting and insights.
Responsibilities
- Develop, scale, and optimize forecasting and scenario planning capabilities to support strategic and operational decisions.
- Evolve measurement programs focused on commercial investment evaluation, forecasting accuracy, and planning effectiveness—especially in trade optimization.
- Evolve optimization analytics to improve resource allocation decisioning (e.g., trade spend, pricing, PPA, promo mix)
- Design, develop, and deploy AI agents within the commercial data and analytics ecosystem to drive automation, productivity, and measurable business impact.
- Implement MLOps and AIOps best practices using Azure Machine Learning, Azure DevOps, and Microsoft Fabric for model lifecycle management, CI/CD, and automated monitoring.
- Collaborate with cross-functional teams to integrate advanced analytics into business workflows and ensure scalability and governance.
- Continuously monitor and optimize models for accuracy, fairness, and compliance with enterprise standards.
- Perform other duties as assigned.
Benefits
- Jack Link’s provides a variety of benefits to eligible Team Members, including medical, dental and vision benefits, life and disability insurance, 401k participation, paid holidays, and paid time off.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
