plaintext
JOB SUMMARY
Our client is seeking a Data Scientist to drive machine learning and optimization initiatives that improve supply chain performance. This role focuses on developing scalable data science solutions that enhance operational efficiency, inventory management, and end-to-end supply chain decision-making. You will work cross-functionally with teams across Merchandising, Supply Chain, Operations, and Customer Insights to identify high-impact opportunities and deliver data-driven solutions that improve the customer and operational journey.

Key Responsibilities
- Partner with business stakeholders across Merchandising, Supply Chain, Operations, and Customer Insights to identify opportunities and define data science use cases that improve operational performance
- Design and develop machine learning models, optimization algorithms, and statistical solutions to solve supply chain challenges
- Build production-ready prototypes and iteratively develop end-to-end data science pipelines
- Develop and deploy scalable solutions leveraging machine learning, artificial intelligence, and advanced analytics techniques
- Collaborate with Product and Technology teams to deploy models into production within an MLOps framework
- Follow SAFe Agile methodology to deliver incremental value and continuously improve models and solutions
- Translate complex data science outputs into actionable insights for business stakeholders
- Monitor model performance and continuously refine solutions based on business feedback and evolving data

Required Qualifications
- Advanced Degree (MA/MS, PhD) in Mathematics, Statistics, Economics, or related quantitative field
- 6+ years of experience developing machine learning, optimization, and statistical solutions using Python, SQL, Databricks, and Azure ML on large-scale datasets.
- Experience building custom algorithms and optimization models beyond standard packaged solutions.
- Strong understanding of retail supply chain operations, including inventory management, demand forecasting, inventory placement, replenishment, safety stock optimization, and fulfillment planning.
- Experience applying predictive modeling and machine learning techniques to solve inventory, forecasting, and operational performance challenges.
- Ability to translate analytical findings into actionable business decisions and measurable operational outcomes.
- Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK
- Experience with Azure Cloud technologies including Azure DevOps, Azure Synapse, MLOps, GitHub
- Solid experience working with large datasets and developing ML/AI systems such as: natural language processing, speech/text/image recognition, supervised and unsupervised learning models, forecasting and/or econometric time series models
- 6+ years of relevant data science experience in an applied role - preferable w/in retail, logistics, supply chain or CPG.

Preferred Qualifications
- Deep Supply Chain & Inventory Optimization Knowledge - Inventory management, inventory placement, demand forecasting, fulfillment planning, safety stock optimization, and predictive inventory modeling.
- Advanced Data Science & Algorithm Development - Ability to build custom machine learning, optimization, and statistical algorithms from scratch.
- Enterprise Data Science Technology Stack - 6+ years of Python, SQL, Databricks, Azure ML, and large-scale data engineering/model deployment experience.
- Key Domain Expertise Successful candidates will demonstrate experience in several of the following areas: - Inventory Management & Optimization - Inventory Placement Strategies - Demand Forecasting - Fulfillment & Shipment Forecasting - Safety Stock Optimization - Predictive Inventory Modeling - Machine Learning & Advanced Analytics for Supply Chain Operations

Certifications
- Azure Data Science Associate, Azure AI, Safe Agile