Aleksandrs Drozdovs
Aleksandrs Drozdovs
Dublin · Maynooth 2026
Open to 2026 roles · Dublin, Ireland

Software engineerwith quant instincts.

Computer Science & Software Engineering graduate (Maynooth, 2026). I ship production systems end-to-end – two live SaaS apps, an agentic AI assistant, a live self-scoring ML forecasting service, and a six-phase pre-registered quant research program. Tested, documented, and honest about the results.

+
Automated tests
Live SaaS shipped
~$K
Live trading profit
Fig. 01 – NASDAQ-100 FYP strategyEquity · in-sample
Jan 2025Feb 2026
+$28,400Net P&L
56.94%Win rate
1.703Profit factor
Selected work

Eight exhibits, one direction.

Fig. 02Live ML · self-scoring

Dublin Bikes Forecast

A live forecasting service that predicts bike and dock availability across all ~115 Dublin Bikes stations at the 08:30 and 17:30 commute windows – and grades itself in public. Every forecast is committed to a git ledger before its target time exists, so the track record cannot be edited or restarted. A pre-registered 28-day gate decides the verdict on the public scoreboard: beat both climatology and persistence baselines with day-clustered bootstrap CIs, or the site says NOT PROVEN. Offline validation cleared all eight confidence intervals before deployment; when the first night’s infrastructure failed, the ledger recorded its own outage as unscoreable – the accounting is the product.

Pythonscikit-learnGitHub ActionsOracle CloudGBFS
Open case study →
K
Training rows
×/day
Live forecasts
days
Public verdict gate
Fig. 03AI agent

JARVIS – voice-controlled AI assistant

A personal AI butler that runs my mornings – now open source. A voice-controlled Iron-Man-style HUD (Electron, with 100% local speech-to-text via whisper.cpp) sits on top of a scheduled, fully unattended agent pipeline: it aggregates my git history, notes, job alerts, and a real bank feed into a grounded morning brief and delivers it to my phone over Telegram at 08:30. Two-way remote commands, headless Claude-agent execution with DPAPI-encrypted credentials, hard safety rules (no financial actions, self-only sends that fail closed), and failure alarms.

Claude agentElectronwhisper.cppPowerShellTelegram Bot API
Open case study →
Fig. 04Full-stack SaaS

Personal Performance OS

A production "operating system" for training, food, habits, and tasks – shipped solo across 145 merged pull requests. Supabase Postgres with Row-Level Security on all 33 tables (28 migrations), Groq (Llama 3.3 70B) coaching hardened against prompt injection, and 790+ automated tests behind CI/CD.

Next.jsTypeScriptSupabaseGroq AI
Open case study →
RLS tables
+
Tests
Merged PRs
Fig. 05Live SaaS · my sport

Maken – AI weight-cut SaaS

A weight-cut platform for judo and BJJ athletes, built by a 16-year black belt for his own sport. Live with alpha users: streaming AI estimates, Upstash Redis rate limiting, Resend email automation, an installable offline PWA, full technical SEO, and GDPR-compliant export and deletion.

Next.js 16SupabaseGroq AIPWA
Open case study →
Fig. 06Quant research

NASDAQ-100 FYP Strategy

Final-year Pine Script v6 strategy for NQ1! E-mini futures using Inverse Fair Value Gaps, Change in State of Delivery, and a liquidity-sweep filter, with fixed risk rules and honestly documented out-of-sample caveats. The sequel (Fig. 07) put this edge on trial – and disproved it.

Pine Script v6TradingViewWalk-forward
Open case study →
%
In-sample win rate
+$K
In-sample P&L
In-sample profit factor
Fig. 07Quant research · capstone

Quant Strategy Research Program

A six-phase, pre-registered research program that settled whether the FYP strategy’s +$28.4K backtest edge was real. Bar-by-bar backtest engine with no lookahead, leak-free walk-forward optimisation, Monte Carlo bootstrap studies, an ML trade-filter experiment, and cluster-bootstrap confidence intervals – verdict decided by a git-timestamped frozen decision table the runner hash-verifies before it will run. Answer: the edge did not survive 10 years and three futures markets, and the gates forensically caught a 60-minute timestamp bug in the source dataset along the way.

PythonpandaspytestStatisticsGitHub Actions
Open case study →
Tests (CI)
OOS trades
yrs
× 3 markets
Fig. 08Quant research

Options Pricing Engine

Three independent option pricers, Black-Scholes closed form, a CRR binomial tree with American exercise, and a seeded Monte Carlo simulation, cross-validated against each other through seven machine-checked numerical gates, all passing to sub-basis-point precision. Then the engine turns on a real SPY option chain and inverts the market's own prices back to volatility: the market quotes a different sigma at every strike, the smile that flat-vol Black-Scholes says is impossible. A live GitHub Pages explorer re-verifies all seven gates on every load.

PythonBlack-ScholesMonte CarloCRR Binomial
Open case study →
7/7
Validation gates pass
2.84e-14
Parity precision
13.6-15.9%
ATM IV smile range
Fig. 09Quant research · applied ML

Alpha Signal Lab

A pre-registered, leakage-audited test of whether a gradient-boosted model beats plain momentum on 5-day cross-sectional equity returns across a 30-name large-cap universe. Twelve point-in-time features, purged walk-forward cross-validation (5-day purge, ~1% embargo), and eight automated leakage-audit tests that all pass against the real pipeline, not mocks. A deliberately leaky control run alongside the honest one shows exactly what overclaiming looks like: honest rank IC 0.0100 versus leaky IC 0.1506, a fifteen-fold inflation from one mistake, shuffling instead of purging. The honest model does not beat momentum, and a follow-up SHAP diagnostic explains precisely why: which feature dominates every fold, and where the model’s picks diverge from momentum’s.

PythonLightGBMSHAPpandasscikit-learn
Open case study →
0.0100 / 0.1506
Honest vs leaky rank IC
8/8
Leakage audits pass
Tests (CI)
Also shipped

Trading Analytics Dashboard

230+ commit full-stack trade journal and market-research app – Next.js dashboard, authenticated trade logging, analytics pages, a Python/FastAPI back end, tests, schemas, and Vercel deployment.

Also shipped

Vectorised Backtesting Engine

Python engine with a strategy registry, slippage/commission model, and walk-forward split. Benchmarks SMA Crossover and RSI Mean Reversion against the FYP strategy; GitHub Actions auto-updates results.

Also shipped

registry-resolve

Entity resolution across three real Irish open-data registers – deterministic ID join where one exists, Splink matching where it doesn’t. Evaluated against 330 blind pairs, Cohen’s kappa 1.000 after a stricter self-imposed bar flagged the first pass as not good enough.

Also shipped

Irish Property Price Index

Mix-adjusted stratified price index on 797,774 real Property Price Register sales (dbt + DuckDB), validated against the CSO. Finds the raw median overstates national growth and understates Dublin’s, opposite signs from the same method.

Also shipped

Speed-to-Lead AI Agent

AI receptionist that catches, qualifies, and books inbound leads in under 60 seconds – free-text chat, an owner dashboard with an ROI readout, and a one-line rebrand config. Public scripted demo; the production design pairs Claude with Supabase and calendar booking.

Also shipped

Monte Carlo Robustness Study

Monte Carlo stress-test of a real 72-trade NQ futures record – bootstrap resampling, order reshuffling, and drawdown-risk distributions, with an honest writeup of what survives.

Also shipped

Polymarket Favourite Bias

Pre-registered backtest over 2,418 resolved Polymarket markets: favourites win 90.6% of the time and still lose ~1% after fees. Verdict: NOT PROVEN.

Also shipped

Football Career Trajectory Model

Pre-registered Monte Carlo projection of young footballers’ careers on 24,057 FBref player-seasons, cross-checked on unseen 2025–26 data at six horizons. Verdict: NOT PROVEN, skilled but under-confident.

Also shipped

jobq, Durable Job Queue

Durable job queue built from scratch in Go, standard library only: at-least-once delivery, actor-per-topic concurrency, a CRC-checked group-committed write-ahead log. A crash harness kills the process cold mid-write across 5 rounds: zero jobs lost, zero acknowledged jobs resurrected.

Also shipped

Ghost Bus Tracker

A 24/7 pipeline that polls Dublin's live GTFS-Realtime feed and classifies every scheduled Dublin Bus / Go-Ahead trip into one of six honest outcomes, grading its own uptime in public alongside the routes it measures. A self-designed feed-health gate caught a real NTA data outage on its first live day and withdrew that day's verdicts rather than publish false accusations.

Also shipped

Job-Hunt Analytics

A month of one graduate’s real job search and AI-assistant operations, parsed from messy markdown trackers into a queryable DuckDB database and published as an anonymised static dashboard. A privacy gate enforced in CI was adversarially attacked and closed on 7 real leak paths before anything went public, behind a 164-test suite. Nine SQL analyses over 50 tracked applications and 65 logged assistant operations, deliberately framed as descriptive rather than inferential at that sample size – every rate published beside its raw numerator and denominator, including the headline: 0 interviews from 50 applications.

Track record

Real work, research, and pressure.

Feb 2025 – Jul 2025 · Maynooth

Quantitative Researcher & Software Engineer (Part-Time)

DLT Capital
  • Built and tested automated Bitcoin and futures trading bots in PineScript on TradingView, encoding systematic entry, exit, position sizing, and risk-management logic.
  • Developed fully rules-based crypto and futures strategies, validated with statistical filters and strict risk controls.
  • Generated approximately $15,000 in live trading profit through disciplined, systematic execution.
Jul 2023 – Apr 2025 · Dublin

Sales Assistant (Part-Time) · Volunteer First Aider

Circle K · Resus First Aid Ireland
  • Ran high-volume POS and cash handling under time pressure, holding accuracy and service standards through peak periods.
  • Volunteer first aider: assess and respond to medical emergencies calmly, documenting incidents to health-and-safety protocol.
Sept 2022 – Sept 2026 · Maynooth, Ireland

B.Sc. (Hons) Computer Science & Software Engineering2:1 Honours

Maynooth University

Two live full-stack SaaS products on Next.js, TypeScript, and Supabase, backed by 790+ automated tests, CI/CD, and Row-Level Security on every table. Final-year project: an automated NASDAQ-100 futures strategy, followed by a six-phase, pre-registered research program that honestly disproved its backtest edge. Industrial placement: DLT Capital.

Machine Learning & Neural NetworksAI & Language ProcessingParallel & Distributed SystemsAlgorithms & Data StructuresSoftware Testing & VerificationDatabases
Certifications
  • Claude Code 101 – Anthropic, 2026
  • Claude Platform 101 – Anthropic, 2026
Toolbox

The stack I can actually work in.

Languages
  • Python
  • TypeScript
  • JavaScript
  • Go
  • Java
  • C++
  • SQL
  • PowerShell
  • PineScript
  • HTML & CSS
Frameworks
  • React
  • Next.js
  • Node.js
  • Express
  • FastAPI
  • pandas
  • NumPy
  • Tailwind CSS
  • Framer Motion
AI & ML
  • LLM integration (Anthropic, Groq)
  • AI agents & tool-use (MCP, Claude Code)
  • Prompt engineering
  • Applied ML & meta-labelling
Testing & Tools
  • Vitest
  • Playwright
  • pytest
  • Git & GitHub Actions
  • Supabase
  • PostgreSQL
  • MongoDB
  • Vercel
  • Jupyter
  • Postman
  • TradingView
The stuff that changes how I work

Composure, tested twice over.

Judo – 16 years, black belt

Multiple Irish national medals, competing from regional to international level. Judo taught me to stay composed when things get ugly, lose without excuses, and improve through relentless repetition – the same temperament I bring to engineering. It also pointed me at a real problem to solve: I built Maken, an AI weight-cut SaaS, for athletes like me.

Algorithmic trading

Funded-account holder with verified real payouts, focused on NASDAQ-100 E-mini futures during NY morning sessions. I write strategies, test assumptions, and execute with predefined risk. It is a useful pressure test for engineering judgment: vague thinking gets punished quickly, and the only thing that survives is a system you can actually trust.

Get in touch

Hiring for 2026? Let’s talk.

Open to graduate software engineering, full-stack, AI, fintech, and data-tooling roles. Best next step is email or LinkedIn.

aleksandrs.drozdovs2005@gmail.com