Turn Data Into Decisions That Drive Revenue

I design and build decision-ready Power BI dashboards that teams can use immediately.
From messy data to clear KPIs, trusted numbers, and confident decisions.

Current Projects

A selection of my recent open-source work and public project contributions, hosted on GitHub.

Vantage Alpin: Analytics Engineering
Production Data Stack

Vantage Alpin: Analytics Engineering

Production financial reporting engine replacing legacy PDF reports with a dynamic, decision-ready Power BI system.

Python dbt DuckDB SQL PowerBI PowerQuery DAX

Concept

This project acts as the central financial reporting engine for Vantage Alpin. It replaces legacy PDF reports with a dynamic Modern Data Stack (MDS) that processes stochastic transaction data into a clean Star Schema.

Features

  • Controlled Stochasticity: Uses Non-Homogeneous Poisson Processes (NHPP) to model realistic demand patterns.
  • Product Economics: Pricing follows Log-Normal distributions; popularity follows Pareto (Power Law).
  • Marketing Attribution: Algorithmic allocation of ad spend to order lines based on revenue share.

Architecture

  • Star Schema: Central fct_transactions table linking to Type 1 SCD product dimensions.
  • Currency Normalization: Robust handling of multi-currency transactions (EUR/CHF) with daily rate lookups.
  • DirectQuery-like Extract: Custom Parquet/CSV export workflow from DuckDB to Power BI for performant local development.
End-to-End SaaS Operating System
Stochastic Financial Twin

End-to-End SaaS Operating System

A full-stack simulation engine that translates static business plans into living data systems.

Excel Python dbt DuckDB SQL Streamlit Prophet

Concept

This project implements a "Rapid Data Function"—instantiating an entire end-to-end data stack (Stochastic Simulation, Data Warehouse, Algorithmic Forecasting, and BI) purely from a static business definition.

Features

  • Stochastic Engine: Simulates Customer Acquisition (Poisson), Retention (Hazard/Survival), and Revenue expansion.
  • Regime-Aware Forecasting: A Prophet model that detects "Growth Regimes" to avoid overfitting on early-stage data.

Architecture

  • Contract-First Engineering: The entire simulation scales dynamically based on a JSON contract extracted from the Excel Operating Plan.
  • Medallion DWH: A rigorous dbt project structure (Bronze/Silver/Gold) ensuring clean lineage.
  • Agentic Build Pipeline: Treating business logic as code, we use cursor/windsurf to scaffold the entire stack from specs.
Interactive Yield Curve Heatmap
DATA VISUALIZATION

Interactive Yield Curve Heatmap

An interactive web application encoding 25+ years of German sovereign yield curve data into a single, high-performance canvas heatmap.

React D3.js Bundesbank API HTML5 Canvas

Concept

A web application that visualizes 25+ years of German sovereign yield curve data in a single view. The application fetches monthly Svensson zero-coupon yield estimates directly from the Bundesbank SDMX REST API.

Features

  • High-Performance Rendering: Uses HTML5 Canvas and ImageData for pixel-level bilinear interpolation, providing smooth and accurate visuals.
  • Interactive Controls: Configurable date and maturity ranges, 26 color palettes, and interactive tooltips for precision exploration.
  • Data Integration: Live data fetching with automatic fallback to a synthetic Nelson-Siegel model dataset if the API is offline.

Architecture

  • Frontend: React 18 for UI and D3 (v7) for color interpolators and scales.
  • Export: On-device high-resolution PNG rendering via an offscreen 2560x1440 canvas.
B2B Pipeline Forecasting Prototype
Predictive Analytics

B2B Pipeline Forecasting Prototype

Business-day sales pipeline forecasting prototype with competing outcomes, age-based conversion kernel estimation, and PIT reconstruction.

DuckDB Python Forecasting Analytics Engineering

Concept

Model how a B2B opportunity pipeline converts over time (in business days), then forecast future daily conversions by combining expected conversions from existing active stock and newly arriving opportunities. Built as a transparent, auditable forecasting framework.

Features

  • Kernel Estimation: Competing-risk kernel estimation (won, lost, censored) from a trailing training window.
  • PIT Reconstruction: Robust Point-in-Time reconstruction from SCD2 status history to prevent look-ahead leakage.
  • Synthetic Data: Generator includes realistic behaviors like business-day seasonality, weekend suppression, and regime switches.

Architecture

  • DuckDB Core: A fast analytics warehouse managing calendar, opportunity facts, and SCD2 status history.
  • Evaluation Framework: Daily error metrics (MAE/RMSE/WAPE) and rolling multi-as-of backtesting with age-attributable error surfaces.
  • Multi-panel Visualization: Structured forecast architecture rendering existing-pipeline and future-arrivals convolution heatmaps.
ShaderGradient Playground
Creative Coding & Graphics

ShaderGradient Playground

A browser-based, real-time shader gradient simulator built on Three.js and custom GLSL for rendering and exporting animating mesh gradients.

Three.js GLSL React Creative Coding

Concept

The playground renders a live, animating gradient mesh using a custom simplex-noise vertex shader. Dial in animated mesh gradient visuals—spheres, planes, water planes—and export them as looping GIFs or videos directly from the browser without any installation.

Features

  • Real-Time Shading: 3 customizable gradient colors blended across geometry based on noise, full lighting/environment controls.
  • Geometry & Camera: Tweak geometries (sphere, plane, etc.), noise displacement, and camera angles freely.
  • Rich Export: Export looping animations as GIFs or videos (WebM/MP4 up to 4K), or copy the exact state as a React JSX snippet.

Architecture

Built purely in the browser using Three.js and custom GLSL. It features an integrated preset system with localStorage, and client-side media encoders (omggif and WebCodecs/MediaRecorder API) for direct asset generation.

Questions? I reply fast.

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