DGM Analytics

Role Mandate

We are looking for a senior analytics leader who can move seamlessly from business problem → analytical hypothesis → solution → execution → measurable impact.

The role will lead complex analytics across Mobility, Broadband/Wi-Fi/FWA, DTH and digital ecosystems, partnering with senior business stakeholders to shape growth, retention, monetization and customer strategy –not simply report what has happened.

Key Responsibilities

• Own the analytics agenda for major business charters spanning acquisition, revenue growth, monetization, churn/retention, CLM and GTM.
• Translate ambiguous business questions into structured hypotheses, analytical frameworks and actionable recommendations, challenging assumptions where required.
• Build behaviour-led customer intelligence using transaction, usage, digital, device, location and engagement signals.
• Lead predictive analytics and ML use cases across propensity, churn, conversion, next-best-action and customer value, ensuring solutions move from development to business adoption.
• Develop micro-cohort, persona and moment-based segmentation to improve targeting, conversion, retention and customer experience.
• Build customer value frameworks, including LTV/CLV, to guide prioritisation, cross-sell, upgrades, offers and retention decisions.
• Drive funnel, app/customer journey and experimentation analytics to identify leakage, design interventions and measure incremental impact.
• Support GTM, distribution and operational planning through demand forecasting, geo-spatial intelligence, serviceability, capacity and resource analytics.
• Build executive-ready decision products, analytical tools and narratives that enable faster, better business decisions.
• Drive cross-functional execution with Marketing, Sales, Product, Technology, Network, Finance and Operations, with clear governance and impact tracking.
• Build analytics capability through coaching, problem-solving standards, knowledge sharing and ownership of business outcomes.

Core Skills & Competencies

Business & Strategic Thinking

Understands commercial drivers, frames the right problems and connects analytics to revenue, churn, CX and other business KPIs.

Advanced Analytics

Strong command of statistics, predictive modelling, segmentation, propensity, experimentation and impact measurement.

Customer Intelligence

Derives behavioural insight from heterogeneous customer and digital signals and converts it into actionable cohorts and interventions.

Storytelling & Influence

Simplifies complex analysis into compelling management narratives and influences senior stakeholders toward action.

Execution & Ownership

Drives problems from hypothesis through implementation, adoption and realised business impact.

People Leadership

Builds high-performing teams, develops talent and creates independent problem solvers.

Curiosity & Innovation

Explores new data, ML/AI methods and ways of working while constructively challenging existing approaches.

Technology & Analytical Stack

• Advanced SQL, Python and PySpark for large-scale data extraction, transformation, modelling and analytical automation.
• Strong experience with machine learning, predictive modelling and applied AI.
• Familiarity with GenAI, LLM-based applications and agentic AI is preferred.
• Experience with large-scale data platforms such as Spark, Databricks, Snowflake, BigQuery or equivalent.
• BI and visualization tools such as Tableau or Power BI, with emphasis on decision-oriented rather than descriptive reporting.
• Experience with app/event analytics, attribution, experimentation and campaign/CLM platforms.
• Exposure to geo-spatial analytics and location intelligence is an advantage.
• Strong understanding of data quality, metric governance, model validation and analytical controls.
• Ability to work with APIs, automated pipelines and version-controlled analytical workflows.

Experience & Education

• 8+ years of relevant experience across Business Analytics, Customer Analytics, Data Science, Marketing Analytics, Consulting or similar data-intensive consumer businesses.
• Proven experience leading analytics teams and complex cross-functional programmes.
• Undergraduate or postgraduate qualification in Engineering, Analytics, Statistics, Economics, Management or a related discipline.

Success Measures

The role will be judged by business impact rather than volume of analysis: revenue and ARPU uplift, acquisition and conversion improvement, churn reduction, CLM effectiveness, customer value creation, speed-to-insight, adoption of analytics solutions, quality of decision-making and development of a strong analytics organization.

Why This Role Matters

This is a builder's role. The successful candidate will make analytics a strategic decision layer for the business – combining customer understanding, ML/AI and commercial judgement to uncover opportunities that conventional reporting misses and taking them through to execution and scale.

This is cleaner and closer to your real technical profile.