I am a Fellow of the Institute of Actuaries and having recently completed my taught PGCAP with distinction, am now also a Fellow of the Higher Education Academy.
I have just recently completed work as a Senior Lecturer in Actuarial Science and was the Programme Director for the BSc. in Actuarial Science at Queen Mary University of London (QMUL), a Russell Group University.
I also lectured on the MSc. In Business Analytics on a module called Programming for Business Analytics, which I wrote myself. This module was extremely popular with students scoring high module evaluations and earning me a third place spot of all postgraduate lecturers in the School of Mathematics in my first year as a Lecturer!
I approach education as a collaborative exercise - I believe that every student can learn the material but sometimes it is a question of motivation and belief. For me the "penny-drop" moment when a student understands something they previously had not (or thought they could not) is the reason I teach and these moments are very rewarding.
As well as being a seasoned Academic I have over 15 years of industry experience - mainly through my own consultancy business. I worked primarily as an Actuary in the City of London across several insurance companies in varied and interesting roles including: Statistics, Financial Modelling, Python Coding, VBA coding, Excel model development, SQL database builds and, of course, Financial Reporting.
I am comfortable teaching any of the Institute and Faculty of Actuaries (IFoA) examinations, Computer Science and Statistics but specialise in:
Frequentist and Bayesian Statistics
Machine learning (Computational Statistics)
Python (PyCharm and Jupyter in particular)
Microsoft Products (In particular Excel, Access, VBA and Power BI)
Availability: Anytime weekdays or weekends.
Willing to travel: Home Only
Experience: Queen Mary University of London (Senior Lecturer)
I have written and delivered three modules at QMUL at both undergraduate and postgraduate levels
Through the Student feedback process, I have achieved extremely high module scores for This module is well taught.
Actuarial professional development II: is a zero-credit module that was proving unpopular with students. After discussions with my class and some redesign it now scores 4.4 / 5.0 with students calling it "very useful". For this module I invited several leading industry figures to give guest lectures establishing long-term relationships with industry.
Programming for Business Analytics: Is a Postgraduate module on the popular Masters in Data Analytics and also the Masters in Business Analytics. This module was written by me with entirely my own lecture material (off the top of my head!). It is a popular course having scored 4.7 / 5.0 and 4.6 / 5.0 in its two module evaluations going into its third year. The first time I taught this course it was block-taught in six days, this was an unpopular format with students and led to complaints about this condensed method of study. Despite the student reservations I scored high enough to rank me third of all postgraduate lecturers in our school and the highest of all of the lecturers on this Masters programme. The module teaches a capstone analytics project analysing human resources data to predict likelihoods of employees leaving the company based on various predictors. The technologies used are Microsoft (Excel, Access, SQL, VBA).
Statistics for insurance: This is an undergraduate statistics module which forms part of Institute of Actuaries exemption recommendations (part of the CS2 exemption). I wrote all of the notes (in the form of LaTeX slides and tutorials) and delivered it for the first-time last year scoring a 4.4 / 5.0.
The overwhelming majority of module evaluations I have received cite both the lecturer and the material as being the best things about that module.
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