Here's what you'll do:
- Lead the design, development, and deployment of advanced machine learning models across key areas such as forecasting, replenishment, and fraud detection
- Partner with product, engineering, and analytics teams to define and deliver data-driven features and insights within CIN7’s platform
- Build and maintain end-to-end ML pipelines in production environments (from data ingestion to monitoring and retraining)
- Translate complex business problems into structured, machine-learnable challenges
- Drive a culture of experimentation and evidence-based decision-making
- Mentor and guide a growing team of data scientists and ML engineers
- Stay ahead of the curve in applied AI/ML, especially in the fields of supply chain, time series forecasting, and decision intelligence
Here's what you'll bring with you:
- 4+ years of experience in data science or machine learning, including at least 2 years in a leadership or principal role
- Proven track record of delivering production-grade ML systems in a SaaS or product-driven company
- Deep understanding of ML techniques (supervised, unsupervised, time-series, probabilistic models, deep learning, etc.)
- Strong programming skills in Python and experience with frameworks like scikit-learn, TensorFlow, or PyTorch
- Familiarity with Azure cloud platform and data/ML ops tools (e.g., Airflow, MLflow, Docker, Kubernetes)
- Experience working with large structured datasets, ideally in domains like logistics, inventory, retail, or manufacturing
- Excellent communication skills and ability to influence across cross-functional teams
These are some nice-to-have skills:
- Experience with supply chain optimization, inventory control systems, or ERP integrations
- PhD or Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field
- Familiarity with pricing algorithms, recommendation systems, or operations research methods
- Knowledge of Azure platform
In return, we offer:
- Make a global impact: help shape the future of 8,500+ businesses worldwide
- Be part of a rapidly growing SaaS scale-up with a strong data and product culture
- Competitive salary
- Remote-friendly and flexible work environment
- Professional development budget and growth opportunities
- Smart, collaborative team solving meaningful problems

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