Senior Manager, Data, Analytics & AI

Primary Responsibilities:  

Strategic Leadership

• Define and execute a forward-looking Data, Analytics, and AI strategy aligned to enterprise goals and digital transformation priorities.
• Establish an integrated data and AI roadmap that unites data governance, analytics, and intelligent automation under a cohesive vision.
• Serve as the internal champion for AI adoption – educating leaders, identifying use cases, and driving responsible implementation of advanced technologies

Data & Analytics Excellence

• Lead enterprise data architecture, governance, and quality programs to ensure trusted, secure, and accessible data across all systems.
• Evolve the BI landscape through modern visualization tools, cloud data platforms, and self-serve analytics that empower business decision-makers.
• Partner with functional and technical teams to design and deliver data pipelines, predictive models, and advanced analytics solutions that drive measurable business outcomes.

AI Innovation & Enablement

• Identify and prioritize AI and machine learning opportunities that improve operational efficiency, customer experience, and business insight.
• Oversee the design, development, and deployment of AI models and intelligent applications – ranging from demand forecasting and personalization to natural language and generative AI use cases.
• Collaborate with business leaders to integrate AI into core workflows and decision processes.
• Ensure ethical, secure, and responsible AI in alignment with company governance and compliance standards.

Leadership & Collaboration

• Lead, mentor, and develop a high-performing data team.
• Foster a culture of innovation, curiosity, and accountability within the Data & AI organization.
• Partner cross-functionally with Sales, Operations, Marketing, Finance, and other departments to ensure data and AI capabilities deliver measurable business value.
• Manage vendor relationships, technology investments, and budgets for data and analytics platforms.

Key Skills:

• Expertise in data engineering, data warehousing, data governance, and enterprise data architecture.
• Strong experience with BI and data visualization tools (ex: Sigma, Power BI, Qlik) and modern data platforms (ex: Snowflake, Databricks, Azure Synapse).
• Demonstrated success in implementing AI/ML technologies, including large language models (LLMs), generative AI, predictive analytics, and/or data science toolkits (Python, SQL, Azure ML, etc.).
• Deep understanding of data integration, APIs, and cloud ecosystems supporting AI and advanced analytics.
• Strong communication and presentation skills with the ability to influence at all levels of the organization.
• Demonstrated ability to work across multiple teams to evaluate new ideas, discuss technical concepts, establish priorities and timelines, make tradeoffs, and remove roadblocks.
• Ability to lead, manage and build a high-performing team in a remote work setting.
• Proficiency in one or more of the following technologies is beneficial but not required: Snowflake, SQL, Python, Sigma, Coalesce

Desired Skills and Experience:    

• 8+ years of experience in data management, analytics, or IT leadership roles, with at least 3 years leading data or AI-focused teams.
• Proven success in building and scaling enterprise analytics or AI programs, preferably in a multi-national, consumer packaged goods (CPG), or manufacturing environment.

Education and Certifications:

• Bachelor’s degree in computer science, Data Science, Software Engineering, Information Systems or equivalent experience (Masters preferred).

Minimum Physical and Environmental Requirements:         

• Visual Abilities: Specific vision abilities required by this job include close vision, peripheral vision, depth perception, and ability to adjust focus, read reports, create presentations and use a computer system.
• Hearing: Ability to effectively communicate with co-workers, vendors, and students.
• Dexterity, Grasping, Feeling: Write, type and use the telephone, copier, and computer systems.
• Mobility: Open files and operate office machines; move between departments and attend meetings.
• Talking: Frequently convey detailed or important instructions and ideas accurately, loudly, or quickly.
• Work in a remote or hybrid environment
• Using a standard computer keyboard and monitor
• Work has deadlines, multiple interruptions and may be stressful at times
• Work may require occasional travel