Campbell Soup
Vice President Of Data, Analytics, And Ai
Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao's Homemade, Snack Factory, Snyder's of Hanover. Swanson, and V8. Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us. Campbell Soup Company (Nasdaq CPB) is a multinational food company headquartered in Camden, NJ. It is driven and inspired by its purpose
"Connecting People Through the Food They Love". For generations, people have trusted Campbell to provide authentic, flavorful, affordable foods and beverages that connect them to each other, to warm memories, and to what's important today. Campbell's portfolio is focused on two distinct businesses: Campbell Meals and Beverages and Campbell Snacks. Campbell Simple Meals and Beverages, which houses the Campbell's, Swanson, Chunky and Pacific soup and broth brands as well as V8 juices, Rao's, Prego, and Pace Mexican sauce, among others. Campbell Snacks, home to well-known brands such as Pepperidge Farm and Milano cookies, Goldfish crackers, Snyder's of Hanover pretzels, Kettle and Cape Cod chips, Lance crackers and Late July organic tortilla chips; The strategy is one of focused differentiation anchored in value creation. This focus enables it to leverage its iconic brands and strong positions in the market where it has the greatest presence. Campbell's is being reshaped to drive sustainable growth and enhance shareholder value by implementing a dual mandate to strengthen their core business and expand into higher-growth spaces. We are seeking a dynamic and forward-thinking Vice President of Data, Analytics, and AI to lead the development of enterprise-wide data strategy and capabilities that empower our teams with fast, frictionless access to actionable insights. In this high-impact leadership role, you will architect the vision and execution of modern data and AI strategies across the Consumer-Packaged Goods (CPG) value chainfrom commercial operations to supply chain optimization. This role will lead a team of data scientists, data engineers, and analytics professionals to build scalable platforms and predictive models that drive data-informed decisions, operational efficiency, and consumer personalization. This role combines strategic leadership with deep technical fluency across data platforms, data science, machine learning, and enterprise-scale data engineering. Key Responsibilities: Data & Analytics Strategy: Develop and implement a comprehensive strategy that leverages data science, AI (GenAI, Agentic), self-service and data engineering to drive innovation and support CTDO and business objectives. Focus on maximizing the value of existing data assets and creating frameworks for scalability and reusability. Data Science: Drive the development and deployment machine learning models, ensuring that advanced analytics are embedded in the decision-making processes across the organization. Build data science teams to deliver RGM, Trade planning, Customer segmentation for Marketing, High accuracy demand forecasting, Market mix modeling for Finance and Predictive maintenance, Ultimate Control Tower for Supply Chain. Data Engineering: Oversee the development and maintenance of scalable data infrastructure, including data lakes and pipelines, to support robust analytics and AI initiatives. Data Management: Lead efforts around data governance, data quality, and data security, ensuring that data is accurate, accessible, and compliant with regulatory standards. Establish common semantic layer for single source of truth and create frame work to generate Synthetic data for competitive advantage. AI (Gen AI, Agentic): Guide the team and deliver custom or vendor-based AI (Gen AI, Agentic AI ) solutions for used cases which increases the productivity of the employees. Create the framework to measure and optimize the accuracy of these solutions which helps the stakeholders to get adopted. Business Intelligence: Consolidate Visualization tools, build a Center of Excellence on Business Intelligence to reduce the insights quality issues. Establish Self-service layer and create guard rails such that the data and insights generation are democratized. Team Development: Build and scale high-performing data teams, cultivating a culture of innovation, collaboration, and continuous improvement. Build the internal brain in the D&A department to develop and support the advanced solutions. Vendor Management: Strategically manage relationships with key external vendors such as Microsoft, Databricks and Consultancy vendors, while working to build internal capabilities that reduce dependency on external partners. Cross-Functional Collaboration: Work closely with other senior leaders within the IT department and with business stakeholders to ensure alignment between data initiatives and broader business goals. Strategic Leadership Design and implement the enterprise data, analytics, and AI roadmap aligned with company goals. Serve as the executive champion for data-driven decision-making and self-service analytics across all business functions. Partner with senior leaders in IT to support marketing, sales, supply chain, HR and finance to identify high impact use cases for data and AI. Technical Leadership & Architecture Oversee development of modern, cloud-native data infrastructure (e.g., Snowflake, Databricks, etc) to enable real-time analytics and scalable data storage. Guide deployment of enterprise data pipelines using xxxx or similar technologies. Lead design of analytical and ML models using Python, R, SQL, and frameworks. Champion use of modern BI tools (e.g., Power BI, Tableau, xxx) to democratize data access and insight delivery. AI & Advanced Analytics Drive applied machine learning initiatives for core CPG use cases such as: Demand forecasting and inventory optimization Revenue Growth Management Trade promotion effectiveness Customer segmentation and personalization Predictive maintenance in manufacturing Promote responsible application of ethical AI practices, ensuring transparency, bias mitigation, and governance. Data Governance & Operations Work with the enterprise data governance team to define and enforce robust data governance, security, and data quality frameworks across all systems and processes. Ensure compliance with global data privacy regulations (e.g., GDPR, CCPA). Monitor performance of data systems and analytics initiatives, delivering continuous improvement and ROI tracking. Organizational Development Build and scale high-performing, cross-functional teams spanning data engineering, data science, analytics, and platform operations. Promote data literacy and enablement across the organization through training, workshops, and change management initiatives. Required Qualifications: Experience: 15+ years of progressive leadership experience in data science, AI, data engineering, and advanced analytics within a large-scale, complex organization (preferably large CPG industry experience). Technical Skills: Deep expertise in cloud-based data platforms (AWS, Azure) and AI/ML frameworks. Strong knowledge of data architecture, data lakes, data warehouse, and managing Peta bytes of data. (preferably Databricks) Experience with data pipelines, model operationalization and managing data operations, Solid experience in managing a large BI instance supporting various functions across Manufacturing/Supply Chain/R&D/Marketing/Corporate. Expertise in building and managing self-service analytics environment. Implemented Gen AI solutions either internally built or external vendor solution using the newer Large Language Models. Expertise in building AI agents to improve employee productivity Productionize experience of large data science solutions such as Pricing, Demand Forecasting, Customer segmentation, Control Tower, Market Mix Modeling & Trade Promotion Management. Track record of delivering data products and platforms that enable enterprise-scale analytics and AI adoption. Preferred Experience: Experience in a CPG, retail, or manufacturing environment with complex supply chains and high SKU volumes. Familiarity with real-time analytics, data mesh architectures, and composable data stacks. Exposure to AI/ML model deployment and MLOps pipelines Compensation and Benefits: The target base salary range for this full-time, salaried position is between $256,600-$368,900. Individual base pay depends on work location and additional factors such as experience, job-related skills, and relevant education or training. Total pay may include other forms of compensation. In addition, we offer competitive health, dental, 401k and wellness benefits beginning on the first day of employment. Please ask your Talent Acquisition Partner for more information about our
Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao's Homemade, Snack Factory, Snyder's of Hanover. Swanson, and V8. Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us. Campbell Soup Company (Nasdaq CPB) is a multinational food company headquartered in Camden, NJ. It is driven and inspired by its purpose
"Connecting People Through the Food They Love". For generations, people have trusted Campbell to provide authentic, flavorful, affordable foods and beverages that connect them to each other, to warm memories, and to what's important today. Campbell's portfolio is focused on two distinct businesses: Campbell Meals and Beverages and Campbell Snacks. Campbell Simple Meals and Beverages, which houses the Campbell's, Swanson, Chunky and Pacific soup and broth brands as well as V8 juices, Rao's, Prego, and Pace Mexican sauce, among others. Campbell Snacks, home to well-known brands such as Pepperidge Farm and Milano cookies, Goldfish crackers, Snyder's of Hanover pretzels, Kettle and Cape Cod chips, Lance crackers and Late July organic tortilla chips; The strategy is one of focused differentiation anchored in value creation. This focus enables it to leverage its iconic brands and strong positions in the market where it has the greatest presence. Campbell's is being reshaped to drive sustainable growth and enhance shareholder value by implementing a dual mandate to strengthen their core business and expand into higher-growth spaces. We are seeking a dynamic and forward-thinking Vice President of Data, Analytics, and AI to lead the development of enterprise-wide data strategy and capabilities that empower our teams with fast, frictionless access to actionable insights. In this high-impact leadership role, you will architect the vision and execution of modern data and AI strategies across the Consumer-Packaged Goods (CPG) value chainfrom commercial operations to supply chain optimization. This role will lead a team of data scientists, data engineers, and analytics professionals to build scalable platforms and predictive models that drive data-informed decisions, operational efficiency, and consumer personalization. This role combines strategic leadership with deep technical fluency across data platforms, data science, machine learning, and enterprise-scale data engineering. Key Responsibilities: Data & Analytics Strategy: Develop and implement a comprehensive strategy that leverages data science, AI (GenAI, Agentic), self-service and data engineering to drive innovation and support CTDO and business objectives. Focus on maximizing the value of existing data assets and creating frameworks for scalability and reusability. Data Science: Drive the development and deployment machine learning models, ensuring that advanced analytics are embedded in the decision-making processes across the organization. Build data science teams to deliver RGM, Trade planning, Customer segmentation for Marketing, High accuracy demand forecasting, Market mix modeling for Finance and Predictive maintenance, Ultimate Control Tower for Supply Chain. Data Engineering: Oversee the development and maintenance of scalable data infrastructure, including data lakes and pipelines, to support robust analytics and AI initiatives. Data Management: Lead efforts around data governance, data quality, and data security, ensuring that data is accurate, accessible, and compliant with regulatory standards. Establish common semantic layer for single source of truth and create frame work to generate Synthetic data for competitive advantage. AI (Gen AI, Agentic): Guide the team and deliver custom or vendor-based AI (Gen AI, Agentic AI ) solutions for used cases which increases the productivity of the employees. Create the framework to measure and optimize the accuracy of these solutions which helps the stakeholders to get adopted. Business Intelligence: Consolidate Visualization tools, build a Center of Excellence on Business Intelligence to reduce the insights quality issues. Establish Self-service layer and create guard rails such that the data and insights generation are democratized. Team Development: Build and scale high-performing data teams, cultivating a culture of innovation, collaboration, and continuous improvement. Build the internal brain in the D&A department to develop and support the advanced solutions. Vendor Management: Strategically manage relationships with key external vendors such as Microsoft, Databricks and Consultancy vendors, while working to build internal capabilities that reduce dependency on external partners. Cross-Functional Collaboration: Work closely with other senior leaders within the IT department and with business stakeholders to ensure alignment between data initiatives and broader business goals. Strategic Leadership Design and implement the enterprise data, analytics, and AI roadmap aligned with company goals. Serve as the executive champion for data-driven decision-making and self-service analytics across all business functions. Partner with senior leaders in IT to support marketing, sales, supply chain, HR and finance to identify high impact use cases for data and AI. Technical Leadership & Architecture Oversee development of modern, cloud-native data infrastructure (e.g., Snowflake, Databricks, etc) to enable real-time analytics and scalable data storage. Guide deployment of enterprise data pipelines using xxxx or similar technologies. Lead design of analytical and ML models using Python, R, SQL, and frameworks. Champion use of modern BI tools (e.g., Power BI, Tableau, xxx) to democratize data access and insight delivery. AI & Advanced Analytics Drive applied machine learning initiatives for core CPG use cases such as: Demand forecasting and inventory optimization Revenue Growth Management Trade promotion effectiveness Customer segmentation and personalization Predictive maintenance in manufacturing Promote responsible application of ethical AI practices, ensuring transparency, bias mitigation, and governance. Data Governance & Operations Work with the enterprise data governance team to define and enforce robust data governance, security, and data quality frameworks across all systems and processes. Ensure compliance with global data privacy regulations (e.g., GDPR, CCPA). Monitor performance of data systems and analytics initiatives, delivering continuous improvement and ROI tracking. Organizational Development Build and scale high-performing, cross-functional teams spanning data engineering, data science, analytics, and platform operations. Promote data literacy and enablement across the organization through training, workshops, and change management initiatives. Required Qualifications: Experience: 15+ years of progressive leadership experience in data science, AI, data engineering, and advanced analytics within a large-scale, complex organization (preferably large CPG industry experience). Technical Skills: Deep expertise in cloud-based data platforms (AWS, Azure) and AI/ML frameworks. Strong knowledge of data architecture, data lakes, data warehouse, and managing Peta bytes of data. (preferably Databricks) Experience with data pipelines, model operationalization and managing data operations, Solid experience in managing a large BI instance supporting various functions across Manufacturing/Supply Chain/R&D/Marketing/Corporate. Expertise in building and managing self-service analytics environment. Implemented Gen AI solutions either internally built or external vendor solution using the newer Large Language Models. Expertise in building AI agents to improve employee productivity Productionize experience of large data science solutions such as Pricing, Demand Forecasting, Customer segmentation, Control Tower, Market Mix Modeling & Trade Promotion Management. Track record of delivering data products and platforms that enable enterprise-scale analytics and AI adoption. Preferred Experience: Experience in a CPG, retail, or manufacturing environment with complex supply chains and high SKU volumes. Familiarity with real-time analytics, data mesh architectures, and composable data stacks. Exposure to AI/ML model deployment and MLOps pipelines Compensation and Benefits: The target base salary range for this full-time, salaried position is between $256,600-$368,900. Individual base pay depends on work location and additional factors such as experience, job-related skills, and relevant education or training. Total pay may include other forms of compensation. In addition, we offer competitive health, dental, 401k and wellness benefits beginning on the first day of employment. Please ask your Talent Acquisition Partner for more information about our