Senior Specialist: Quantitative Analyst

Details

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Role Purpose/Business Unit:

This role supports the Consumer Business Unit (CBU) Postpaid team by preparing advanced decision-making models/tools and analytics to aid product implementations and commercial and financial performance across all Postpaid business initiatives. The candidate will be responsible for optimising and automating daily and monthly reports/ models to improve team efficiency and modelling accuracy. The candidate will collect data and business strategy from all relevant stakeholders/teams and integrate them into the budget and rolling forecast process consistently. The suitable candidate will demonstrate excellent communication and collaboration skills to successfully guide and manage different stakeholders from products, pricing, commercial and finance through performance insights and commercial and/or financial levers to support executive and senior management strategic objectives.

Your responsibilities will include:

Advance Analytical Support

Collect, integrate, and store raw data from different sources into the Teradata platform in collaboration with Big Data to facilitate insight-building.

Create and set up automated and optimised tables in Teradata to support daily and monthly automation.

Build and automate budget models and/or daily and month-end reporting.

Seek opportunities to improve business processes; models and systems by identifying and recommending effective ways to operate and adding value to the Postpaid and FBP team.

Contribute to the development of differentiated; superior solutions that meet stakeholder and business requirements through analytical insights.

Supporting business continuity plans through upskilling junior team members and knowledge accessibility, through the creation of centralised data repositories for “how to” manuals, industry trends and best practice templates.

Building financial models, analysing customer trends/behaviour.

Discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, econometrics, and database systems

Identify key trends - identify & predict impact of potential risk factors

Identify causal impact and attribution.

Analyse POCs and market tests – Post implementation reviews on products/customer responses/pricing

Model and predict the future performance of users and/or products.

Utilisation of intelligent methods to extract data patterns — the overall goal of which is to extract information from a dataset, and transform it into an understandable structure for further use in terms of quantifying financial impact.

Perform sensitivity analysis by stress testing models

Driving Business Impact

Collaborate and work closely with cross-function business partners to identify performance gaps & approach problem-solving in a structured manner.

Create insightful presentations and analysis that tell a story with a focus on insights and actions, not just data.

Synthesize methodology and data into actionable business strategy and communicate findings to product, sales, and management teams – drive action and subsequent tracking, with support for implementation.

Month End

Customer analytics on Postpaid P&L movements to explain financial impacts – analysis of surplus.

Pro-actively identify key risks on the basis that it will potentially impact performance