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Presentation
I build end-to-end systems that turn raw data into decisions —
from pipeline architecture to deployed dashboards to causal
evidence that holds up in regulated environments.
CORE CAPABILITIES
Causal Inference & Risk Analytics
• Difference-in-differences, event studies, synthetic controls
• Bayesian posterior estimation for policy impact measurement
• Financial volatility modelling: GARCH, VaR, spectral analysis
Production Forecasting & ML
• Hybrid econometric-ML ensembles (ARIMA + GARCH + XGBoost/CatBoost)
• Automated retraining pipelines via Airflow, containerised with Docker
• Hyperparameter optimisation (Optuna), pseudo-labelling, ensemble methods
NLP & Document Intelligence
• Policy document parsing, structured extraction, compliance automation
• Topic modelling (LDA), sentiment analysis, TF-IDF/cosine similarity
• Text classification, recommender systems, BeautifulSoup scraping
SELECTED WORK
→ African Economic Intelligence Pipeline | BigQuery · dbt · Airflow
48 countries, 8 indicators, 24 years. World Bank API → BigQuery →
dbt Cloud → Airflow → Power BI. Dockerised, live.
Stack: Python · SQL · R · BigQuery · dbt · Airflow · Docker ·
Git/GitHub · PostgreSQL · MySQL · Tableau · Power BI ·
Streamlit Cloud · Looker Studio · Hadoop · Hive
Availability: Fully remote · Immediate start
Rate: $60–90/hour | Project retainers preferred
from pipeline architecture to deployed dashboards to causal
evidence that holds up in regulated environments.
CORE CAPABILITIES
Causal Inference & Risk Analytics
• Difference-in-differences, event studies, synthetic controls
• Bayesian posterior estimation for policy impact measurement
• Financial volatility modelling: GARCH, VaR, spectral analysis
Production Forecasting & ML
• Hybrid econometric-ML ensembles (ARIMA + GARCH + XGBoost/CatBoost)
• Automated retraining pipelines via Airflow, containerised with Docker
• Hyperparameter optimisation (Optuna), pseudo-labelling, ensemble methods
NLP & Document Intelligence
• Policy document parsing, structured extraction, compliance automation
• Topic modelling (LDA), sentiment analysis, TF-IDF/cosine similarity
• Text classification, recommender systems, BeautifulSoup scraping
SELECTED WORK
→ African Economic Intelligence Pipeline | BigQuery · dbt · Airflow
48 countries, 8 indicators, 24 years. World Bank API → BigQuery →
dbt Cloud → Airflow → Power BI. Dockerised, live.
Stack: Python · SQL · R · BigQuery · dbt · Airflow · Docker ·
Git/GitHub · PostgreSQL · MySQL · Tableau · Power BI ·
Streamlit Cloud · Looker Studio · Hadoop · Hive
Availability: Fully remote · Immediate start
Rate: $60–90/hour | Project retainers preferred
🛠️
Offered services
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Stock/Portfolio Volatility Analysis — GARCH + VaR
GARCH(1,1) conditional volatility, Value-at-Risk (95% and 99%), and rolling volatility windows for any ticker or portfolio. Delivered as PDF report + Excel file with charts. Ideal for investment ...
200 $
🎨
Forecast With Uncertainty Bands — ARIMA/SARIMA
ARIMA or SARIMA model with 80% and 95% prediction intervals. Includes model diagnostics (residual checks, ACF/PACF) and plain-English summary of trend vs. seasonality components. Delivered as ...
180 $
✂️
Sales/Demand Forecast
Historical trend + seasonality forecast for sales, inventory, or demand. Delivered as CSV of point forecasts + Excel chart showing actual vs. predicted. 48-hour turnaround. Good for budgeting and ...
120 $
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Background
Adminstrative Assistant
• Dashboards & Reporting: Designed and maintained KPI dashboards in Tableau and Excel tracking risk indicators, compliance metrics, and portfolio performance — used daily by leadership
• Compliance: Operated within FAIS and FSCA regulatory frameworks — AML/KYC monitoring, suspicious activity flagging, full audit trail documentation
• Customer Segmentation: Conducted segmentation using K-Means clustering and logistic regression — identified distinct risk profiles informing portfolio management strategy
• Compliance: Operated within FAIS and FSCA regulatory frameworks — AML/KYC monitoring, suspicious activity flagging, full audit trail documentation
• Customer Segmentation: Conducted segmentation using K-Means clustering and logistic regression — identified distinct risk profiles informing portfolio management strategy
Bachelor of Information Technology- Data Science
Bachelor of Economic Science
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Working hours
Monday ▪ Today
From08h00To18h00
Tuesday
From08h00To18h00
Wednesday
From08h00To18h00
Thursday
From08h00To18h00
Friday
From08h00To18h00
Saturday
Closed
Sunday
Closed
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