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ne-he/README.md

Nehemiah Wilhelmus Junaidi

Data Science undergraduate at BINUS University (full scholarship), based in Jakarta. I work on applied machine learning and data products, and I care more about shipping something people can actually open than about notebooks that stay on my laptop.

Currently available for remote contract or part time work in data analysis, dashboards, and applied ML.


What I build

Retrieval and LLM systems Hybrid retrieval (dense embeddings + BM25 with reciprocal rank fusion), confidence gating so the model declines instead of hallucinating, and streamed answers with citations. Built on Gemini embeddings and Supabase pgvector.

Data analysis and dashboards Turning messy exports (marketplace CSVs, survey results, spreadsheets nobody wants to touch) into interactive dashboards. Python, pandas, Streamlit, plotly.

Model deployment Getting models out of the notebook: FastAPI services, containerised inference, AWS SageMaker, Hugging Face Spaces.


Selected projects

Project What it does Live
agentic_verdict Agentic data analyst with a causal decision engine: sandboxed code execution, self verification, method routing across A/B, observational and time series designs. open
pulse Real time Jakarta air quality platform. Streaming ingestion, online forecasting with river, drift triggered retraining.
RAG_businessAnalysis_assist FinSight. Answers questions about a public company strictly from its SEC 10-K filings, with section aware chunking, hybrid retrieval, and a confidence gate that declines instead of guessing.
URL_Detection PhishGuard v2. URL phishing detection API, MiniLM embeddings into a Keras classifier, with strict input validation and a label orientation regression test. open
nemi-dashboard E-commerce sales analysis over 20,848 orders, aimed at three owner decisions: which products to grow, which regions are failing, and where margin leaks. open
Feature_shopz Feature store with a PostgreSQL offline store, a Redis online store, FastAPI serving, and freshness and drift monitoring. open
Addictv2 CatBoost regressor behind one shared preprocessor so training and serving cannot drift apart. SHAP, tests, CI, Docker. open
iceberg v2 Scroll driven 3D web CV: a snowfield, a crevasse, then a live-rendered ice cave. React Three Fiber, drei, a world generated from noise. open
web_portofolio_RAG Ask Nemi. A resume you talk to instead of read: hybrid retrieval over pgvector, confidence gating, streamed answers with citations. open

Tools I reach for

Python pandas NumPy scikit-learn PyTorch CatBoost Streamlit SQL FastAPI Supabase / pgvector Redis Docker MLflow AWS SageMaker React TypeScript


Contact

Open to conversations about data work, research assistance, and remote internships.

Pinned Loading

  1. Feature_shopz Feature_shopz Public

    An end-to-end e-commerce feature store. Batch-computes 20+ user-level features into a PostgreSQL offline store and a Redis online store, serves them over FastAPI, and watches freshness and drift wi…

    Python 1

  2. URL_Detection URL_Detection Public

    PhishGuard v2.2, a layered phishing URL detector: a live blocklist, a curated allowlist, then a MiniLM plus lexical-feature model. 95.7% accuracy and 95.8% recall on a 1,000-URL holdout, failure mo…

    TypeScript 1

  3. RAG_businessAnalysis_assist RAG_businessAnalysis_assist Public

    FinSight v1, the original Python prototype of a SEC 10-K RAG engine. Superseded by the rewrite in ne-he/finsight-v2.

    Python 1

  4. iceberg iceberg Public

    A scrollable 3D web CV. One continuous camera descent through a live-rendered glacier in React Three Fiber, with real refraction and clickable ice built from Blender assets.

    JavaScript

  5. agentic_verdict agentic_verdict Public

    VERDICT ANALYST, an agentic data analyst with a causal decision-science engine. Sandboxed code execution, self-verification, method routing (A/B, observational, time-series), and assumption diagnos…

    Python

  6. pulse pulse Public

    Real-time Jakarta air-quality ML platform. Streaming ingestion, online forecasting (river), anomaly detection, drift-triggered retraining, auto model cards, and LLM incident cards.

    Python