$109,400 – $150,400
Listed on Pepperidge Farm’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Campbell's is seeking a hands-on senior data scientist to build and deploy machine learning and statistical models that drive business impact across supply chain, marketing, finance, and R&D. The role combines individual technical contribution with mentorship of junior team members and collaboration with cross-functional stakeholders to translate complex data challenges into production-ready analytics products.
Our summary, not Pepperidge Farm’s wording. The full posting is on their site.
Skills this role names
- A/B Testing
- Databricks
- Deep Learning
- Docker
- Git
- Machine Learning
- MLflow
- NumPy
- Pandas
- Python
- PyTorch
- R
- scikit-learn
- SciPy
- Snowflake
- SPARK
- SQL
- Statistical Modeling
- TensorFlow
- XGBoost
Log in to see which of these are already on your profile.
What they ask for
Required
- Master's degree in Statistics, Computer Science, Mathematics, Engineering, Operations Research, or related quantitative field, or equivalent practical experience
- 4+ years developing and deploying advanced analytics, machine learning, and statistical models in production environments
- Strong foundation in probability, statistics, supervised and unsupervised learning, forecasting, experimentation, causal inference, and optimization
- Advanced proficiency in Python and/or R with experience building scalable, modular, tested, version-controlled solutions
- 2+ years working with SQL and modern data platforms such as Snowflake, Databricks, Spark, or comparable technologies
- Experience developing and deploying machine learning solutions using standard libraries and frameworks
- Experience with MLOps and software engineering best practices including Git, Docker, MLflow, CI/CD processes, and production support
- Ability to design experiments, establish success metrics, quantify business impact, and communicate findings to technical and non-technical audiences
- Strong problem-solving, stakeholder management, and communication skills
- Demonstrated experience leading complex projects and mentoring junior team members
Nice to have
- PhD in Statistics, Computer Science, Mathematics, Engineering, Operations Research, or related quantitative discipline
- Experience with optimization modeling and tools such as Gurobi or PuLP
- Experience with cloud-based analytics and machine learning platforms, particularly Microsoft Azure including Databricks, Synapse, AKS, Azure Functions, and cloud storage
- Experience building analytical applications, dashboards, or decision-support tools using Power BI, Tableau, Plotly Dash, or similar technologies
- Familiarity with feature stores, advanced production MLOps frameworks, and large-scale model governance practices
- Experience within Consumer Packaged Goods, retail, or related industries
- Expertise in demand forecasting, pricing and promotions, marketing mix modeling, assortment optimization, trade spend analytics, or supply chain optimization
- Experience contributing to recruiting, training, and capability-building initiatives within data science or analytics organizations