Muhammad Bavla

First Class BSc (Hons) Actuarial Science & Mathematics graduate with 5 IFoA exemptions

Talent

London, Greater LondonMember since March 1, 2026

PythonStatistical modellingForecastingData analysisScenario analysisStochastic processesSurvival analysisFault-findingRoot-cause analysis

Hire this person

Send a job offer directly to this candidate

PythonStatistical modellingForecastingData analysisScenario analysis

About

First Class BSc (Hons) Actuarial Science & Mathematics graduate from the University of Manchester (82% average) with 5 IFoA exemptions (CS1, CS2, CM1, CB1, CB2). Strong technical background in statistical modelling, stochastic processes, survival analysis and financial risk modelling, with practical experience using Python, R and Excel to analyse uncertainty and support data-driven decision making.

Seeking Graduate

Actuarial opportunities within General Insurance Pricing, Reserving, Capital Modelling or Life & Reinsurance.

Experience

Intern at Government Statistical Service (2024-06 – 2024-08)

Led an independent data analysis project of a dataset exceeding 100,000 observations using R, developing forecasting models to analyse fiscal outcomes under uncertainty.
Built models incorporating macroeconomic variable and distributional assumptions, improving projection accuracy.
Performed scenario analysis and stress testing to assess extreme outcomes and downside risk, identifying key drivers of variation and model uncertainty.
Analysed volatility and model uncertainty, identifying key drivers of variation in projections and interpreting statistical results to support evidence-based decision making.
Collaborated with stakeholders including KPMG and IBM to align modelling assumptions, analytical requirements and data outputs.
Delivered reports translating complex statistical outputs into clear insights for decision-making under uncertainty