Associate CO Data & Analytics Product Manager

Unilever•Trumbull, CT

1d•$88,600 - $133,000

About The Position

ABOUT CUSTOMER OPERATIONS DATA & ANALYTICS Customer Operations Data & Analytics partners with business functions and global teams to deliver scalable, automated analytics solutions aligned with enterprise data strategy and One Source of Truth principles. JOB PURPOSE This role is critical to advancing Customer Operations toward a tech-forward, AI-enabled operating model, enabling the design and deployment of scalable analytics products that connect business strategy with enterprise data and technology capabilities. It drives faster and more accurate insight-led decision-making, improved service levels, and end-to-end visibility, strengthening our ability to deliver customer-centric, data-driven outcomes and respond to evolving market needs. Additionally, it accelerates experimentation, innovation, and adoption of AI/ML solutions while building sustainable internal capability and scaling reusable and certified analytics products. Ultimately, this role creates tangible value for the organization by enabling better service on shelf, stronger customer and consumer experiences, and measurable business outcomes that fuel profitable growth. Drive the design, development, and deployment of scalable data and analytics products that enable business transformation across Customer Operations. This role connects business strategy with data and technology, embedding new ways of working, accelerating adoption, and delivering measurable impact through innovative analytics solutions.

Requirements

Bachelor’s degree in data engineering, Supply Chain, Analytics, or related field
3+ years of experience in supply chain with a clear competence in analytics, digital technology (e.g., advanced analytics, AI-enabled platforms), and technology.
Proficiency with programming languages (e.g., SQL, Python, PySpark, Scala)
Experience with visualization platforms (e.g., Power BI, Tableau) and enterprise data ecosystems (e.g., Azure, Google Cloud)
Strong product-oriented mindset with experience delivering end-to-end analytics solutions from concept to deployment
Ability to translate business needs into scalable, high-impact technical solutions
Strong project management skills with the ability to manage multiple priorities and drive outcomes
Excellent communication skills with the ability to influence and collaborate across cross-functional teams
Ability to work seamlessly across business, product, and engineering teams to drive aligned outcomes
Strong stakeholder management with the ability to navigate complex environments
Results-oriented with a strong ownership mindset and accountability for delivery
Proactive problem solver with the ability to develop dynamic, innovative solutions
Continuous improvement mindset with a focus on collaboration, agility, and learning
Self-starter with curiosity and a strong drive to learn and grow

Nice To Haves

Familiarity with enterprise systems (e.g., SAP) is preferred

Responsibilities

Define and drive the Data & Analytics capability strategy aligned to Customer Operations priorities, digital transformation goals, and enterprise data strategy
Design, develop, and scale reusable, certified analytics products that enable faster, more accurate, insight-led decision-making across Customer Operations.
Leverage enterprise data platforms, AI/ML capabilities, and modern analytics technologies to create scalable solutions that connect business strategy with data and technology.
Partner with business stakeholders, product teams, and engineering teams to translate business needs into deployable, high-value analytics products.
Establish standards, governance, and best practices to ensure sustainable product development, quality, scalability, and adoption.
Lead data, analytics, and AI-enabled transformation initiatives that advance Customer Operations toward a tech-forward operating model.
Drive experimentation, innovation, and adoption of AI/ML, automation, and advanced analytics solutions to solve business challenges and unlock new opportunities.
Act as the bridge between business, product, and engineering teams, ensuring alignment of priorities, roadmaps, and execution.
Strengthen end-to-end business visibility and customer-centric decision-making through scalable digital and analytics capabilities.
Build internal capability and foster a data-driven culture by championing modern analytics practices, innovation, and continuous learning.
Drive measurable business outcomes through analytics solutions, including improved service levels, operational efficiency, decision quality, and customer outcomes.
Lead change management efforts to accelerate adoption of new analytics products, AI-enabled tools, and data-driven ways of working.
Develop training, enablement, and upskilling programs to build sustainable internal analytics capability across Customer Operations.
Establish governance frameworks to prioritize investments, track value realization, and manage the analytics product lifecycle.
Continuously optimize products and solutions based on business feedback, performance insights, changing market needs, and emerging technology opportunities.