BN 001

Daniel Wooster

Data Science | AI Engineering
LONDON / NOTTINGHAM • GITHUB • LINKEDIN
02

ABOUT ME

I started programming after a period of travel and independent study. I taught myself the fundamentals and became interested in how code can turn ideas into working systems. Since then, I've focused on building practical projects and steadily improving my technical skills.

My projects are my discography, each one just as unique as the next, solving problems I've encountered or ideas that I find interesting. I thrive in environments where I can constantly learn and grow.

When I'm not at the keyboard, you'll find me at the other keyboard practising piano or at the climbing wall (still stuck at v5).

Education: BSc Computer Science & AI with Year in Industry, University of Nottingham, 2024-2028. Year 2 average: 71% (first-class band).

2028
Degree ends
Jul 2026
Placement start
25+
Platinum trophies
03

SKILLS

GROUPED BY WHERE I USED THEM

SKILL GROUPS

Hover or focus a key to preview. Click it, or press Enter, to lock it and see where I used those skills.

04

PROJECTS

GREATEST HITS

reviews L0 Thrawn: system architect L1 Vader: router, read-only L2 Five domain agents L3 Droideka: read-only reviewer

AGENTIC

A personal operating system for planning and research: provider-neutral Markdown context plus eight Claude Code subagents in a four-layer hierarchy. Rules in the repository keep the reviewer agent read-only and stop agents from grading their own work. A correction log records agent mistakes. GitHub Actions checks for file structure, agent frontmatter and secrets are configured.

Hierarchy diagram

Select a node to see its role and tool limits.

Claude Code Subagents Markdown GitHub Actions
Diagram: Astora Risk is the hub. Astora Grants is the first product built on it. ASTORA RISK shared hub ASTORA GRANTS first product

Astora Risk

A hub for compliance tools that analyse financial transactions synced from accounting software (Xero and QuickBooks, via OAuth 2.0). A deterministic rules engine uses fuzzy string matching and confidence-scored heuristics to categorise transactions. The multi-tenant backend has token encryption, role-based access control and PDF and CSV report generation. Astora Grants is the first product built on it: it tracks UK charity restricted funds against grants and produces funder-ready reports.

In development. Looking for charities that need it.

Python FastAPI React PostgreSQL OAuth 2.0
Titanite Signal Builder screen: a list of three master signals and an editor for a signal named Macro Tech Crash Warning, with four conditions on the 10-year Treasury yield, VIX, S&P 500 and Warsh sentiment.
Signal Builder (click for full size)
Titanite Intel Hub screen: a news feed with bullish, bearish and neutral tags and ticker badges, next to a Fed transition watch panel.
Intel Hub (click for full size)

Local build; some feeds mocked.

Titanite

A single-tenant, Bloomberg-style dashboard for tracking high-volatility tech stocks and macro risk signals. The Signal Builder composes Boolean rules from metrics such as EMA crosses, VIX, TNX and gold. The Intel Hub merges Finnhub and Google News RSS feeds. A Congress Tracker for US Senate and House stock disclosures is planned. A human-machine loop sends SEC filings and earnings transcripts through agentic LLM extraction, then a manual audit, before a conviction score and tier are set.

v1 built; 2.0 rebuild in progress, local-only.

Next.js TypeScript Python Finnhub Google News RSS

Blue Note Tuner

An iOS instrument tuner. Real-time pitch detection uses the YIN algorithm through AudioKit, with transposition offsets for Concert, Alto Sax, Tenor Sax and Trumpet. MVVM architecture.

Swift SwiftUI AudioKit

Also built: Statify, a Spotify stats app (React, Flask, Spotify Web API).

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WORK EXPERIENCE

PAST & PRESENT GIGS

July 2026
PRESENT

LexisNexis Risk Solutions

Data Science Undergraduate Placement
  • Built workflow-specific agents for the team, including a Streamlit-specific agent and a presentation agent, and helped optimise the AI workflow by improving the efficiency of agent outputs to cut cost and credit use.
  • Analysed client data with Python and SQL in Snowflake: client health checks, policy and rule evaluations, and complex fraud case studies.
  • Worked across client organisations on policy optimisation, health checks, model updates and new feature additions.
  • Built internal Streamlit applications and interactive Snowflake dashboards for fraud metrics and client data.
Python SQL Snowflake Streamlit Agentic workflows
June 2025
August 2025

Footprints CEC

Systems Engineer Intern
  • Developed a K-means clustering model for donor segmentation, with data cleaning, feature engineering and visualisation of the results.
  • Removed over £300 in annual SaaS overhead by migrating the CRM from Salesforce, configuring Google Workspace and Meta Ads, and deploying a new e-commerce and event platform.
K-means clustering CRM migration Google Workspace

Earlier

2020
2023

Le Table D'Alix

Kitchen Porter

Washing dishes, cleaning the kitchen, and assisting the chefs.

Caffeine addiction Pain tolerance Stoicism
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CONTACT

GET IN TOUCH

Get in touch about the projects above, data science or agentic AI systems.

DW RECORDS
DOWNLOAD CV