Senior Analytics Product Manager

Sysco is building Analytics & Performance Intelligence capabilities that help teams turn data into measurable business value. As a Senior Analytics Product Manager in Houston, TX 77001 (onsite), you will help define strategy and lead analytics product development and deployment across multiple use cases powered by one of Sysco’s core enterprise analytics engines.

This is a customer-first role supported by advanced analytics and digital transformation initiatives. You will work closely with executive leadership, business functions (including Merchandising, Revenue Management, and Human Resources), operating companies, specialty businesses, geographic teams, and technology partners to deliver actionable insights that influence real outcomes.

Responsibilities

• Define and align the organization around where Sysco wins and loses by leveraging insights from across the Enterprise Analytics Team (EAT), including Data Science, Primary Research, and Market/Customer Intelligence.
• Set the analytical approach and guide the design and development of models that support multiple business use cases tied to core enterprise analytics platforms.
• Partner with leadership teams to identify business opportunities and develop analytical strategies to address them.
• Conduct data mining, cleansing, transformation, and analysis across large, complex datasets from multiple sources.
• Identify required data sources and elements while maintaining accuracy, completeness, and consistency.
• Resolve data quality issues such as missing, corrupt, irrelevant, or incongruent data.
• Collaborate with Business, Data Science, and Technology teams to ensure analytical models are scalable and deployed effectively across the enterprise.
• Develop performance metrics, reporting frameworks, and tracking mechanisms to measure value realization from analytics solutions.
• Coordinate and lead cross-functional teams made up of analysts, business subject matter experts, and technical resources.
• Translate analytical findings into actionable insights and recommendations for strategic business decisions.
• Drive adoption of analytics capabilities and support a data-driven culture across the organization.
• Support continuous improvement of analytics methodologies, tools, and processes.

Requirements

• Bachelor’s degree in an analytical field such as Engineering, Mathematics, Statistics, Economics, Business, or a related discipline.
• MBA or advanced degree preferred from a top-tier educational institution.
• 5+ years of experience in a corporate environment or leading professional services organization in analytical, strategy, finance, insights, consulting, or related roles.
• Experience working with large datasets and using advanced analytical techniques to solve business problems.
• Experience leading cross-functional initiatives involving business stakeholders, analytics teams, and technology organizations.
• Proven ability to develop analytical frameworks that influence strategic business decisions.
• Hands-on experience with data mining, data cleansing, and data transformation.
• Experience developing business performance metrics, KPI frameworks, and value realization tracking methodologies.
• Experience managing or influencing stakeholders across multiple business functions and organizational levels.
• Ability to translate analytical findings into executive-level presentations and recommendations.
• Strong understanding of digital technologies, data architectures, data ecosystems, and platform interdependencies.
• Knowledge of descriptive, predictive, and prescriptive analytics methodologies and associated tradeoffs.
• Understanding of business value drivers and how analytical modeling decisions connect to business outcomes.
• Excellent problem-solving skills with the ability to structure complex business challenges into analytical frameworks.
• Strong strategic thinking and business acumen, with effective communication across technical and non-technical audiences.
• Ability to manage multiple priorities in a fast-paced environment and demonstrate a commitment to data-driven decision-making and continuous improvement.