Job Description

Job Purpose
The Head of Data, Analytics, and Insights will be pivotal in establishing and leading the data analytics function from the ground up. This role is transformational and entrepreneurial, responsible for embedding a culture of data-driven decision-making across the organization. The role will be essential in developing processes, policies, and RACI models to coordinate how various functions work together and with different business units to serve the overall business.
Key Responsibilities
Strategic Leadership

• Develop and execute a comprehensive data strategy that aligns with business goals and drives value.
• Establish a vision and roadmap for data analytics and insights, transforming the current capabilities into a world-class function.

Team Building and Development

• Recruit, build, and lead a high-performing team of data analysts, data scientists, and researchers to deliver actionable insights that inform data driven decision making.
• Foster a culture of innovation, collaboration, and continuous improvement within the team.
• Provide coaching, mentorship, and professional development opportunities for team members.

Data Infrastructure and Tools

• Implement and manage cutting-edge data infrastructure, tools, and technologies to support analytical needs.
• Ensure the security, privacy, and integrity of data across all platforms.
• Partner with the digital team to implement, onboard all needed infrastructures in a strong data governance environment.

Analytics and Insights

• Work closely with senior stakeholders across the business to understand their needs and objectives, and leverage data from various sources to generate insights that inform decision making, improve customer experience, and optimize marketing campaigns
• Develop advanced analytics models and methodologies to drive business insights and decision-making.
• Conduct in-depth data analysis to identify trends, opportunities, and areas for improvement.
• Deliver actionable insights to key stakeholders, supporting strategic initiatives and business objectives.
• Customer Segmentation: Identify and categorize customers based on behavior, demographics, and purchasing patterns to tailor marketing efforts and improve customer experiences.
• Sales Forecasting: Predict future sales trends and revenue streams using historical data and predictive analytics.
• Market Basket Analysis: Analyze customer purchasing behavior to identify product affinities and optimize cross-selling and up-selling strategies.
• Churn Analysis: Develop models to predict customer churn and identify factors contributing to customer attrition, enabling targeted retention efforts.
• Campaign Performance Analysis: Measure the effectiveness of marketing campaigns and promotions, providing insights into ROI and areas for improvement.
• Inventory Optimization:Analyze inventory levels and sales data to optimize stock levels, reduce costs, and improve supply chain efficiency.
• Customer Lifetime Value (CLV) Analysis:Calculate and predict the lifetime value of customers to prioritize high-value segments and allocate resources effectively.

• Communicate and present complex data and insights in a clear and compelling way to senior stakeholders, using data storytelling and visualization tools
• Collaborate with cross-functional teams, such as Customer Engagement, Marketing, Retail to provide insights and recommendations that support their initiatives and campaigns
• Work closely with key loyalty stakeholders (Manager Customer Engagement) to develop & implement strategies to maximize customer lifetime value through targeted loyalty initiatives

Process and Policy Development

• Develop and implement processes and policies to ensure effective coordination and collaboration between functions.
• Establish RACI models to clearly define roles and responsibilities across the organization.
• Ensure alignment and integration of data analytics and insights functions with overall business objectives.

Stakeholder Management

• Collaborate with internal stakeholders, including executive management teams, CXOs, retail business leads, IT, finance, and operations.
• Serve as the primary point of contact for external stakeholders, including technology partners and data vendors.

Data-Driven Culture

• Promote a culture of data-driven decision-making across the organization.
• Advocate for the use of data and analytics in strategic planning, performance management, and operational improvement.

Minimum Requirements

• Bachelor's degree in Data Science, Business Administration, Statistics, or a related field; MBA or equivalent advanced degree preferred.
• 15+ years of experience leading data and analytics functions preferably in large B2C businesses such as retail, banks, telcos etc.
• Extensive experience in a senior leadership role within data analytics and insights, preferably in the retail sector.
• Proven track record of establishing and leading new functions from scratch.
• Strong strategic thinking, analytical, and problem-solving skills.
• Excellent leadership and team management abilities.
• Exceptional communication and interpersonal skills.
• Ability to thrive in a dynamic and fast-paced environment.
• Proficiency in data analytics tools and software (e.g., SQL, Dataiku Python, R, Tableau, Power BI).
• Experience with data infrastructure and cloud platforms (e.g., AWS, Azure, Google Cloud).
• Knowledge of statistical analysis, machine learning, and data visualization techniques.
• Experience in ML models operationalisation and busness value realisation
• Familiarity with data privacy regulations and best practices.