Manager, Customer Analytics & Insights
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Key skills for this role
About the Role
We are seeking a Manager, Customer Analytics & Insights to establish and lead the data analytics function from the ground up. This transformational role involves developing data strategy, building a high-performing team, and embedding data-driven decision-making across the organization.
Key Skills for This Role
Responsibilities
- Develop and execute a comprehensive data strategy aligned with business goals
- Recruit, build, and lead a high performing team of data analysts, data scientists, and researchers
- Implement and manage cutting edge data infrastructure, tools, and technologies
- Work closely with senior stakeholders to understand needs and generate insights from data
- Develop advanced analytics models and methodologies to drive business insights
- Conduct in depth data analysis to identify trends, opportunities, and areas for improvement
- Deliver actionable insights to key stakeholders supporting strategic initiatives
- Perform customer segmentation, sales forecasting, market basket analysis, churn analysis, campaign performance analysis, inventory optimization, and CLV analysis
- Communicate and present complex data insights to senior stakeholders using data storytelling and visualization
- Develop and implement processes and policies for effective coordination and collaboration
- Establish RACI models to define roles and responsibilities
- Promote a culture of data driven decision making across the organization
Requirements
- Bachelor's degree in Data Science, Business Administration, Statistics, or related field; MBA or equivalent advanced degree preferred
- 12+ years of experience leading data and analytics functions, preferably in large B2C businesses such as retail, banks, telcos
- 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
- 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 business value realisation
- Familiarity with data privacy regulations and best practices
Full Job Posting
Job Purpose
- The Manager Customer 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.
Key Responsibilities
- 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 current capabilities into a world class function.
- Recruit, build, and lead a high performing team of data analysts, data scientists, and researchers.
- Foster a culture of innovation, collaboration, and continuous improvement within the team.
- Provide coaching, mentorship, and professional development opportunities for team members.
- Implement and manage cutting edge data infrastructure, tools, and technologies.
- Ensure the security, privacy, and integrity of data across all platforms.
- Partner with the digital team to implement and onboard all needed infrastructures in a strong data governance environment.
- Work closely with senior stakeholders to understand their needs and leverage data to generate insights.
- 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.
Analytics and Insights
- Customer Segmentation: Identify and categorize customers based on behavior, demographics, and purchasing patterns.
- 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.
- Campaign Performance Analysis: Measure the effectiveness of marketing campaigns and promotions.
- 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.
- Communicate and present complex data and insights in a clear and compelling way to senior stakeholders.
Minimum Requirements
- Bachelor's degree in Data Science, Business Administration, Statistics, or a related field; MBA or equivalent advanced degree preferred.
- 12+ 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 business value realisation.
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