Data Analyst (Fraud) at takealot.com

Your mission, should you choose to accept it:

As a pivotal analytical partner, you will work closely with product managers and engineers to shape innovative features and technologies that elevate the customer experience and drive measurable impact. You will be both independently and jointly accountable for how we measure product performance, define success, and guide teams toward confident, data-informed decisions. Your insights will directly influence roadmap priorities, product iteration, and long-term strategy.

• Driving Product Innovation: Serve as the primary analytical counterpart to product teams, contributing critical insights that inform the development of cutting-edge features and help shape the future of our digital experience.
• Unlocking User Insights: Analyze user behavior and feedback to identify patterns, uncover friction points, and translate findings into actionable recommendations that improve product usability, engagement, and satisfaction.
• Defining Success: Design clear, scalable performance frameworks and KPIs that enable teams to track progress, evaluate product outcomes, and align efforts across disciplines.
• Scaling Experimentation: Build and champion experimentation frameworks, methodologies, and tools that empower product teams to test hypotheses rigorously and iterate with confidence.
• Fostering a Data-Centric Culture: Advocate for data-informed thinking across the organization, promoting best practices and ensuring that product decisions are consistently grounded in evidence and insight.

Qualifications and Experience:

• Bachelor’s Degree, BTech or Advanced Diploma in Information Systems, Computer Science, Mathematics, or Engineering and 3 years of experience in an Analyst or similar analytical role.
• In the event that you do not have a bachelor’s degree or an advanced diploma (in Information Systems, Computer Science, Mathematics, or Engineering), an equivalent experience requirement must be met, which equates to a minimum of 6 years of experience in an Analyst or similar analytical role.
• Proven Experience: 4+ years of hands-on experience as a Data Analyst or in a similar analytical role, ideally within a high-scale e-commerce or digital consumer product environment. Experience supporting product teams across key areas like search, navigation, PDP, cart, or checkout is a strong plus.
• Strategic & Commercial Acumen: Ability to connect the dots between data and business goals, bringing both technical depth and strategic thinking to stakeholder conversations. Comfortable collaborating with commercial, product, and UX teams to guide decision-making and maximize business impact.
• Behavioral Analytics: Demonstrated experience in analyzing onsite user behavior using tools like Google Analytics, Adobe Analytics, or Amplitude to surface actionable insights and track feature adoption and performance.
• Data Proficiency: 4+ years solid expertise in SQL for data extraction and transformation, working knowledge of Python for deeper analysis, modeling, or automation workflows.
• Experimentation Mastery: Strong understanding of A/B testing principles and methodologies, including statistical evaluation and test design. Experience working with experimentation platforms (e.g., Optimizely, Google Optimize, or internal tooling) and guiding teams in setting up and interpreting tests.
• Dashboarding & Data Visualization: Proficient in building and maintaining dashboards using tools such as Tableau, Looker, or Power BI to democratize access to key metrics and enable self-serve insights for stakeholders.
• Data Engineering Fluency: Familiarity with modern data workflows and orchestration tools such as Airflow, dbt, and BigQuery, with a strong understanding of data pipelines, version control (Git), and scalable analytics architecture.
• Communication & Influence: Excellent written and verbal communication skills, with the ability to simplify complex analysis for a variety of audiences. Comfortable presenting to stakeholders at all levels and advocating for data-informed decisions.
• Cross-Functional Collaboration: A team player who thrives in cross-functional environments and contributes actively to the broader Analytics or BI community. Skilled in supporting, challenging, and aligning stakeholders across product, design, engineering, and commercial teams.