60 Snyder Data Scientist Jobs Hiring Near You

HOW YOU WILL MAKE HISTORY HERE...

As a Senior Data Scientist, you will serve as a hands-on technical leader responsible for scoping, developing, and operationalizing advanced statistical, machine learning, and AI solutions that deliver measurable business value for Campbell's. You will partner with business and technical leaders across the organization to transform complex, ambiguous challenges into scalable, production-ready analytics products. Through your expertise, leadership, and mentorship, you will elevate data science capabilities, influence strategic decision-making, and help position Campbell's as a data-driven market leader and preferred retail partner.

WHAT YOU WILL DO...

• Lead the end-to-end development of advanced analytics solutions, including Machine Learning, Deep Learning, Artificial Intelligence, Optimization, Simulation, Data Mining, and Multivariate Statistical techniques such as clustering, regression, PCA, hypothesis testing, and factor analysis.
• Translate complex and unstructured data into actionable insights by sourcing, cleansing, engineering, and validating data while ensuring reproducibility, quality assurance, and model governance.
• Own the deployment, monitoring, and lifecycle management of production models in partnership with Data Engineering and ML Engineering teams, including CI/CD, drift detection, model retraining, and performance monitoring.
• Partner with stakeholders across Supply Chain, Finance, Marketing, Sales, and R&D to identify high-impact opportunities and develop data science solutions that generate measurable business outcomes and ROI.
• Design and lead experimentation strategies, including A/B testing and quasi-experimental approaches, to evaluate business initiatives and support data-driven decision-making.
• Develop compelling visualizations, presentations, and business narratives that translate technical findings into actionable recommendations for senior leadership and non-technical audiences.
• Collaborate with data engineering teams to enhance data and machine learning platforms, evaluate emerging technologies, and recommend improvements that increase scalability, speed, and reliability.
• Mentor and coach junior data scientists through code reviews, methodology guidance, technical leadership, and best practices.
• Contribute to the development of analytics standards, reusable assets, technical documentation, recruiting efforts, training programs, and data science communities of practice across the organization.

WHO YOU WILL WORK WITH...

• Data Science, Data Engineering, and ML Engineering teams
• Supply Chain, Finance, Marketing, Sales, and R&D leaders
• Business stakeholders and decision-makers across Campbell's
• Internal analytics communities and cross-functional project teams
• Senior leadership teams responsible for strategic business initiatives
• External retail partners as part of joint value creation opportunities

WHAT YOU BRING TO THE TABLE... (MUST HAVE)

• Master's degree in Statistics, Computer Science, Mathematics, Engineering, Operations Research, or a related quantitative field; equivalent practical experience will also be considered.
• 4+ years of hands-on experience developing and deploying advanced analytics, machine learning, and statistical models in production environments.
• Strong foundation in data science methodologies, including 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, and version-controlled analytical solutions.
• 2+ years of experience working with SQL and modern data platforms such as Snowflake, Databricks, Spark, or comparable technologies.
• Experience developing and deploying machine learning solutions using libraries and frameworks such as pandas, NumPy, SciPy, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, and statsmodels.
• Experience with MLOps and software engineering best practices, including Git, Docker, MLflow, CI/CD processes, model monitoring, and production support.
• Ability to design experiments, establish success metrics, quantify business impact, and effectively communicate findings to both technical and non-technical audiences.
• Strong problem-solving, stakeholder management, and communication skills with the ability to influence decision-making and drive adoption of analytical solutions.
• Demonstrated experience leading complex projects and mentoring junior team members.

IT WOULD BE GREAT IF YOU HAVE... (NICE TO HAVE)

• PhD in Statistics, Computer Science, Mathematics, Engineering, Operations Research, or a related quantitative discipline.
• Experience with optimization modeling and tools such as Gurobi, PuLP, or similar frameworks.
• Experience with cloud-based analytics and machine learning platforms, particularly Microsoft Azure, including Databricks, Synapse, AKS, Azure Functions, and cloud storage services.
• 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 (CPG), retail, or related industries.
• Expertise in business domains such as 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.