Manager, Advanced Analytics Strategy and Translation

Sysco

About The Position

The Manager, Advanced Analytics Translator advances Sysco’s Analytics & AI capabilities by translating complex business problems into analytics, AI, and decision-intelligence solutions that deliver measurable outcomes. The role collaborates with business stakeholders and Data Science and Technology teams to define decisions, convert business needs into analytical requirements, guide solution development, and embed insights and recommendations into business workflows. The position partners across teams to design and deploy scalable predictive, prescriptive, optimization, and AI-driven solutions; supports data exploration, preparation, and integration; and develops experimentation and measurement approaches to evaluate and improve outcomes. It translates model outputs into actionable recommendations, decision logic, dashboards, and business-facing experiences, while supporting adoption, governance, transparency, and explainability. The role also manages analysts and business partners delivering analytics and decision-support solutions. Estimated time allocation: 30% translating business needs, rules, thresholds, and operational decisions into analytical requirements and decision models; 20% co-designing optimization approaches, decision workflows, and experimentation frameworks; 20% integrating solutions into workflows and driving adoption; 15% measuring outcomes and improving solutions; and 15% supporting decision documentation, governance, transparency, and explainability.

Requirements

Bachelor’s degree in an analytical or quantitative field, such as Engineering, Mathematics, Statistics, Computer Science, Economics, Business, Operations Research, or a related discipline.
At least 3 years of experience in an analytics, strategy, data science translation, product management, finance, or consulting role within a corporate or professional services environment.
Experience translating business problems into analytics requirements and partnering with technical teams to develop data-driven solutions.
Experience defining business KPIs, success measures, or experimentation approaches to evaluate the impact of analytics solutions.
Strong understanding of analytics, AI/ML concepts, data technologies, and business value drivers.
Ability to translate business problems, decisions, rules, and constraints into structured analytical requirements.
Ability to synthesize complex model outputs into business-relevant recommendations and actions.
Understanding of experimentation, model evaluation, KPI development, and outcome measurement.
Working knowledge of predictive and prescriptive analytics, optimization, generative AI, and decision intelligence.
Strong structured problem-solving and cross-functional collaboration skills across Business, Data Science, Product, and Technology.
Excellent communication skills, including the ability to explain analytical recommendations, tradeoffs, and outcomes to technical teams and senior leadership.
Applicants must be currently authorized to work in the United States.

Responsibilities

Translate business problems and decisions into analytical requirements, including objectives, success measures, constraints, rules, and actions, and guide model design for enterprise analytics use cases.
Partner with Business, Data Science, and Technology teams to design and deploy scalable predictive, prescriptive, optimization, and AI-driven solutions.
Conduct data exploration and preparation, identify relevant data sources, and support integration of data required for analytics initiatives.
Design experimentation and measurement approaches, including baselines, KPIs, and feedback loops, to evaluate and continuously improve business outcomes.
Translate model outputs into actionable insights, recommendations, decision logic, dashboards, and business-facing experiences.
Integrate analytics, recommendations, and decision logic into business workflows while supporting transparency and explainability.
Drive adoption and value realization by monitoring solution performance, decision outcomes, and business impact.
Manage analysts and business partners to deliver effective analytics and decision-support solutions.
Translate business needs, rules, thresholds, and operational decisions into analytical requirements and decision models.
Co-design optimization approaches, decision workflows, and experimentation frameworks with Data Science.
Partner with stakeholders to integrate solutions into workflows and drive adoption.
Measure outcomes against baselines and continuously improve solutions.
Support decision documentation, governance, transparency, and explainability.