Senior Data Analyst Digital at MultiChoice

Key Performance Objectives

Analytics, Automation and Engineering

• Perform complex user journey analysis using standard funnels, machine learning, and process mining techniques to understand customer flow through the product.
• Actively extract data from various sources, including Google Analytics, Adobe Analytics, and other data platforms. This includes understanding which areas of the website receive the most attention, tracking the user journey through different pages, and assessing engagement with various elements. By examining these metrics, highlight insights into user preferences, pain points, and opportunities for improving the user experience and optimizing website performance.
• Take responsibility for Digital Product analytics, defining key metrics and collaborating with relevant stakeholders to develop tracking and reporting systems.
• Partner with the Marketing team, providing in-depth analysis on requests and through independent data exploration, offering insights, conversion rates, and interpretations to guide strategic decisions regarding digital product priorities.
• Maintain, build, and improve data consolidation and automation from media platforms, publishers, web analytics, internal data, and CRM platforms to enable an integrated data view.
• Prepare AB testing analysis across multiple channels to understand the impacts of campaigns on customer behaviour.
• Conduct ad hoc deep dive analyses, present results and recommendations to Executives, and provide detailed documentation and informal reports.
• Develop reporting in Tableau, Adobe Analytics, and similar tools to provide business insights.
• Manage stakeholder expectations regarding reporting and the automation of deliverables.
• Create and maintain data models and structures in Data Warehouses and Data Lakes.
• Identify opportunities to improve business processes using modern technologies and automation.
• Modernize and maintain the internal Tableau portal, ensuring high standards of accuracy and usability to drive business decision-making.
• Source, clean, and combine data from various sources to design reports that provide holistic views of the business and its environment.
• Create anomaly detection and alerts for key metrics.

Stakeholder Relations

• Establish and monitor healthy, diverse internal and external relationships, implementing remedial actions as needed to achieve organizational goals.
• Create executive buy-in and trust for digital product and analytics reporting.
• Manage data relationships with external agencies, internal teams, group projects, and consultants.
• Mentor and provide technical guidance to junior team members.
• Share data-related knowledge within the business.

Reporting

• Provide timely and accurate updates, ensuring deliverables are aligned with business and management requirements for specific projects.
• Report on status, risk and timelines regarding projects to provide visibility and line of sight.
• Test data solutions and pipelines (unit testing and system integration testing) and verify that they meets business, functional and technical specifications.

Qualifications

Essential

• Degree in Science/Mathematics/Engineering/Data Science/Data Analysis

Preferred

• Post Graduate qualification in Engineering/Data Science/Business Management

Experience

• 5-8 years in an analytical or engineering field working with large data sets (streaming and batch)
• Excellent analytics skills, SQL capabilities, data mining, data visualization and Python
• Cloud experience – GCP, Databricks
• Experience working with data warehouses/large databases
• Experience with Spark/Hadoop/Big Data Systems/Non-relational Databases/Data Lakes
• Experience in Tableau , Adobe Analytics and Google Analytics
• Maintenance of data integrity and accuracy
• Analyse, report and surface insights and feedback
• Experience working with large data sets including data cleansing and validation
• Ability to identify trends/behaviours from complex data sets and suggest where they can be applied

Technical Competencies

• Analytical skills
• Problem-solving
• Attention to detail
• Communication skills
• Numerical capability
• A/B Testing
• Conversion Rate Optimization
• Customer Journey Optimisation
• Customer Segmentation
• Customer Behaviour
• Data Mining and Management
• Data Warehousing
• Data Visualisation
• Digital Analysis
• Funnel Analysis