About
Data Scientist | Analytics Engineer | Statistician
Introduction
I am Mfundo Monchwe, a Data Scientist, Analytics Engineer, and Statistician with 4+ years of experience solving data problems across finance, healthcare, retail, and mining.
My work covers the full analytical lifecycle: understanding business questions, exploring and validating data, developing statistical or machine-learning models, building analytical applications, and communicating results to stakeholders.
I am particularly interested in work where statistics, machine learning, data engineering, and business decision-making meet. I prefer practical modelling: start with the problem, understand the data-generating process, establish a sensible baseline, validate carefully, and only add complexity when it produces meaningful value.
Education
MSc in Statistics (Cum Laude) | University of KwaZulu-Natal
Aug 2024 – Mar 2026
Dissertation: Spatial and Joint Modelling of Chronic Illness and Household Wealth among South African Adults
Final mark: 75%
My postgraduate research examined health and wealth inequality using advanced statistical modelling, including Generalized Additive Models, Markov Random Fields, spatial modelling, and copula-based joint frameworks.
The work strengthened my interests in statistical inference, spatial data, uncertainty, model interpretation, and research that connects quantitative methods with real socioeconomic questions.
BScHons in Data Science | Sol Plaatje University
Feb 2021 – Dec 2021
Advanced training in data science, statistics, machine learning, programming, and applied analytics.
BSc in Data Science | Sol Plaatje University
Feb 2017 – Dec 2020
Foundation in statistics, mathematics, computer science, programming, and data analysis.
Professional Experience
Data Scientist / Pricing Analyst | Avis Budget
Apr 2024 – Apr 2026 | Isando, Gauteng, South Africa
My role combined data science with pricing and commercial analytics.
- Developed ARIMA-based forecasting models for vehicle termination and maintenance planning using time-ordered historical data.
- Supported pricing and fleet decisions through analytical forecasting work associated with an approximately 11% improvement in profitability.
- Built a machine-learning model to forecast future new-vehicle valuations and support pricing decisions.
- Performed customer profiling and segmentation to identify profitable and loss-making customer groups and analyse associated loss ratios.
- Developed an interpretable credit-risk recommendation system.
- Conducted EDA, data-quality validation, documentation, IRR calculations, and deviation analysis across datasets from six countries.
- Developed a Shiny dashboard for the iLease product to make analytical outputs accessible to business users.
Key themes: pricing analytics · forecasting · customer analytics · credit risk · data quality · business reporting · Shiny
Data Scientist – Consultant | Notto Africa
Apr 2025 – Jul 2025 | Johannesburg, South Africa
- Designed and commercialised a credit-scoring model using customer financial data.
- Exposed model predictions through a REST API for integration with the wider platform.
- Integrated Explainable AI (XAI) so predictions could be interpreted rather than treated as black-box scores.
- Implemented Keycloak-based authentication and authorisation for secure model access.
- Built a Streamlit application for real-time interaction with model predictions.
Key themes: credit scoring · model deployment · REST APIs · XAI · Streamlit · Keycloak
Data Scientist – Freelancer | Arena Holdings
Oct 2024 – Jan 2025 | Johannesburg, South Africa
- Delivered commercial reporting, predictive modelling, and data-engineering support.
- Built analytical and visualisation workflows for editorial data.
- Translated analytical outputs into reporting that could be used by non-technical stakeholders.
Key themes: reporting · predictive analytics · data engineering · visualisation
Trainee Data Analyst | Auditor-General of South Africa
Mar 2024 – Apr 2024 | Pretoria, South Africa
- Provided data analytics support across multiple audit business units.
- Investigated operational datasets and contributed to data-quality and analytical work.
- Developed analytical models and supported comprehensive audit reporting.
Key themes: audit analytics · data quality · reporting · stakeholder support
Freelance Data Scientist | Remote / International Client Work
Feb 2023 – Aug 2023
- Analysed FASTQ and VCF files from RNA and exome sequencing, including quality control and variant annotation.
- Investigated treatment effects on inflammatory RNA expression using statistical significance testing.
- Conducted A/B testing, ANOVA, CFA, SEM, and hypothesis testing for applied research and retail use cases.
- Produced statistical analysis reports on co-morbidities, genomics, and business data.
Key themes: bioinformatics · statistical testing · research analytics · Python · R
Academic Tutor | Sol Plaatje University
Mar 2021 – Nov 2021
Tutored Big Data Foundations and Introduction to Python Programming to second-year students, covering data structures, data wrangling, analysis, visualisation, and Python problem-solving.
Skills
Programming & analytics
- Python
- pandas
- NumPy
- SQL
- R
- Scikit-learn
- XGBoost
- TensorFlow
- Git / Bash
Data science & statistics
- Exploratory Data Analysis (EDA)
- Data cleaning and validation
- Statistical modelling
- Time-series forecasting
- Classification and regression
- Customer segmentation
- Pricing analytics
- Credit risk
- Hypothesis testing
- A/B testing
- ANOVA
- CFA and SEM
- Bayesian methods
- Spatial modelling
Data delivery & engineering
- REST APIs
- Analytical pipelines
- Streamlit
- Shiny
- Keycloak
- Model interpretation / XAI
- Data visualisation
- Business reporting
Applied domains
- Finance and credit risk
- Automotive and pricing analytics
- Retail and customer analytics
- Mining
- Healthcare and bioinformatics
- Computer vision
- NLP and text analytics
Independent Technical Development
Modern AI Engineering | 2026
I am actively building a structured, hands-on learning repository around modern AI engineering. My focus is on understanding how contemporary AI systems work end-to-end rather than treating LLMs as isolated chat interfaces.
Current areas include:
- Generative AI and LLM fundamentals
- API-based versus local-model workflows
- Retrieval-Augmented Generation (RAG)
- Knowledge-base grounding and controlled responses
- Tool calling
- Agentic AI
- Multi-step AI workflows
Research & Publications
I am a published researcher with work spanning probabilistic machine learning and computer security. My current research interests also include spatial statistics, joint health-wealth modelling, and applied statistical learning.
Contact
I am open to conversations around data science, analytics engineering, statistical modelling, machine learning, applied AI, and research collaboration.
- Email: diditmfundo@gmail.com
- LinkedIn: linkedin.com/in/mfundo-monchwe-48883314a
- GitHub: github.com/Mfundo-debug