Data Scientist - Supply Chain

Compunnel Inc.; Grand Rapids (MI); On-site; USD 90,000 - 140,000; Full time

Job summary

Compunnel, Inc. seeks a Data Scientist to drive machine learning and optimization initiatives that enhance supply chain performance, including inventory management and forecasting across merchandising, supply chain, operations, and customer insights.

You will build production‑ready data science pipelines, deploy models in production within an MLOps framework, and collaborate with cross‑functional teams to translate findings into measurable business outcomes.

Qualifications

• Advanced degree in a quantitative field is required.
• 6+ years applying ML, optimization, and statistics on large datasets using Python, SQL, Databricks, and Azure ML.
• Experience building custom algorithms and optimization models.
• Strong understanding of retail and supply chain operations including inventory management and forecasting.
• Experience translating analytical findings into actionable business decisions.
• Hands-on experience with Azure cloud technologies and MLOps.
• Experience with NLP, forecasting, time-series models, or other ML/AI systems.
• 6+ years in applied data science in retail or logistics preferred.

Responsibilities

• Identify opportunities and define data science use cases to improve operational performance.
• Design and develop ML models, optimization algorithms, and statistical solutions.
• Build production-ready prototypes and end-to-end data science pipelines.
• Develop and deploy scalable ML solutions leveraging AI and analytics.
• Collaborate with Product and Technology to deploy models in production within an MLOps framework.
• Follow SAFe Agile methodology to deliver incremental value and refine models.
• Translate complex outputs into actionable insights for stakeholders.
• Monitor model performance and refine solutions based on feedback.

Skills

Python

SQL

Databricks

Azure ML

Azure DevOps

Azure Synapse

MLOps

PySpark

NumPy

Pandas

Scikit-Learn

TensorFlow

PyTorch

Time-series modeling

Education

MA/MS/PhD in Mathematics/Statistics/Economics or related quantitative field

Tools

Azure DevOps

Azure Synapse

MLOps

GitHub

Databricks

SAS

Job description

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 within 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