Build, optimize, and deploy scalable forecasting models that support pricing, promotions, and assortment strategies across multiple product categories
Apply advanced statistical, machine learning, and deep learning methods (e.g., ARIMA, Prophet, gradient boosting, LSTMs, hybrid ensembles) for forecasting at SKU, category, and chain levels
Implement robust MLOps practices for model deployment, monitoring, and retraining using cloud platforms (Azure, GCP, AWS)
Integrate multiple internal and external data sources (e.g., coupon redemption, merchandising, competitive, and macroeconomic data) into forecasting pipelines
Collaborate with data engineering to ensure scalable, high-quality data pipelines
Partner with business stakeholders in pricing, promotions, and assortment to design and validate forecast-driven decision workflows
Coach and mentor junior data scientists, sharing best practices in forecasting, MLOps, and applied analytics
Monitor forecast accuracy, perform backtesting, and refine models to reduce error rates and improve stability
Develop frameworks for scenario planning and simulation to measure business impact of promotions, pricing strategies, and assortment changes

Requirements

7+ years of experience in data science, forecasting, or applied predictive modeling
4+ years of experience building and deploying time-series forecasting models using methods such as ARIMA, Prophet, gradient boosting, LSTMs, or hybrid ensembles
4+ years of experience with Python and SQL for large-scale data processing
3+ years of experience with MLOps tools and practices (e.g., GitHub/GitLab, Docker, Kubernetes, Kubeflow, CI/CD pipelines)
3+ years of experience using cloud platforms (Azure, AWS, or GCP) and distributed computing frameworks (e.g., Databricks, Spark)
Proven track record of deploying at least 2 production forecasting models that delivered ≥10% improvement in accuracy (e.g., reduction in MAPE, WMAPE, or sMAPE
Experience working with cross-functional teams (engineering, merchandising, pricing, assortment) to deliver at least 2+ enterprise-level data-driven solutions from design to production

Benefits

Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

forecasting modelsARIMAProphetgradient boostingLSTMshybrid ensemblesMLOpsPythonSQLtime-series forecasting

Soft Skills

collaborationcoachingmentoringcommunicationproblem-solvingdecision-makinganalytical thinkingteamworkleadershipstakeholder engagement