Financial Outcomes

Data Strategy and Governance: Develop and execute a comprehensive data strategy aligned with business goals, driving data-driven decision-making across all departments. Establish data governance policies, standards, and processes to ensure data accuracy, integrity, security, and compliance.

Data Management: Oversee data acquisition, storage, quality, and integration from various sources to create a unified and reliable data ecosystem. Collaborate with IT and data engineering teams to design and implement data infrastructure and architecture that supports scalability and agility.

Customer Service

Collaboration and Communication: Work closely with executive leadership to align technology initiatives with business goals. Collaborate with cross-functional teams to identify and address opportunity area s needs. Work closely with stakeholders to gather requirements and translate them into architectural solutions. Communicate complex data concepts to non-technical stakeholders, fostering a culture of data literacy and utilization.

Internal Processes

Analytics and Insights : Drive the development & adoption of advanced analytics, AI & ML & business intelligence capabilities to provide actionable insights for operational improvements, market trends, and customer behavior. Foster the use of predictive and prescriptive analytics to optimize supply chain, sales forecasting, and marketing strategies.

Platform Architecture: - Define and drive the platform architecture strategy to ensure scalability, modularity, and alignment with business objectives. Collaborate with software engineering teams to design and implement the architecture of software applications, ensuring they are efficient, maintainable, and secure. Lead the evaluation and adoption of new technologies, tools, and frameworks to enhance the companys technical capabilities.

Regulatory Compliance: Stay current with data protection and privacy regulations (e.g., GDPR, CCPA) and ensure the companys data practices adhere to legal requirements.

Innovation and Learning

Innovation and Transformation: Identify opportunities to leverage data and emerging technologies (e.g., AI, machine learning) to innovate products, processes, and customer experiences. Lead cross-functional teams in designing and implementing data-driven initiatives that generate value and competitive advantage.

Provide strong leadership to the infrastructure and architecture teams, fostering a culture of collaboration, innovation, and continuous improvement. Set clear goals, mentor team members, and provide guidance for their professional growth. Stay updated with industry trends and emerging technologies to continuously enhance the companys analytics & AI capabilities.

Talent Management : Build and lead a high-performing data and analytics team, attracting top talent and developing skills to meet evolving business needs. Provide coaching, mentoring, and professional development opportunities to team members.

What are the Critical success factors for the Role

Bachelors or Masters degree in Data Science, Analytics, Computer Science, Business, or related field

Proven experience (15+ years) in a senior data leadership role

Strong practitioner of Machine learning and AI technologies

Demonstrated success in crafting and executing data & AI/ML strategies that drive business growth and innovation

Familiarity with the consumer goods industry, domain knowledge, leading analytics & AI for a small to mid-size organization

Expertise in data governance, data quality management, data architecture, and data security.

Excellent communication skills with the ability to engage and influence stakeholders at all levels

Strategic thinker with the ability to translate business needs into actionable data solutions

What are the Desirable success factors for the Role

Familiarity with relevant data regulations and compliance standards.

Vice President - Data & Analytics