I build trading bots, data pipelines and AI workflows that turn market data into decisions. Freelance consultant since 2025, active investor across ETFs, crypto and real estate.
I am Mathieu Haye, 22, based in the Paris region. Freelance consultant in CRM, data engineering and applied AI since October 2025. Background in Economics & Management, then Digital Innovation, now heading into the MSc Data & AI for Finance at Albert School x Mines Paris-PSL.
I build end-to-end data products: trading bots, scoring pipelines, decision dashboards, AI workflows. I invest actively in ETFs, crypto and real estate, and I model what I buy. The next step is to add the quantitative foundation that makes all of this rigorous.
Bloomberg Terminal (BMC), ALM basics, fixed income, portfolio management, ETF / crypto, real estate modeling.
pandas, numpy, scipy, scikit-learn, SQL, ETL, APIs, scraping. Power BI, Looker Studio.
Claude API, prompt engineering, AI scoring, n8n workflows (93+ nodes), Make, Apps Script.
Salesforce (Admin, Apex, SOQL, LWC), Pipedrive, HubSpot, Brevo, Odoo.
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Mean reversion on BTC and ETH with RSI + Bollinger entries. Paper ran +3.2% over 90 days. Live pilot ended at -2.1%: taker fees plus slippage ate the edge. Next iteration on maker-rebate orders.
Personal multi-asset tracker (crypto, stocks, ETF) with technical indicators, AI-generated commentary on market open/close, DCA tracker and Telegram alerts.
TradingView indicator for long-term stock picking: bounce detection, trailing 15% stop loss, higher timeframe candles. Backtest on AAOI (5y): +187%, 54% WR, PF 1.62, MaxDD 24%. Trades return for drawdown protection, not alpha.
Tooling to compare SCI / IS vs LMNP regimes, model mortgage scenarios, and rank French cities on a rental yield index. Used to size my own portfolio.
Fully automated weekly newsletter: ingest from 20+ sources, AI scoring & summarisation, HTML rendering, delivery via Brevo. Runs on autopilot, no human in the loop.
Aggregates WTTJ, JobTeaser and LinkedIn via APIs, applies a weighted scoring algorithm against my profile. For each high-scoring offer, auto-generates an ATS-optimised CV and cover letter in PDF, tailored to the job description.
Salesforce build-out for the 3018 child protection hotline: Apex REST APIs, Lightning Web Components, 3CX telephony integration, Einstein Bot triage and CSP rules.
Two-year apprenticeship inside the ALM team of a public development bank, supervised by a senior ALM financial pilot. Paired with the MSc Data & AI for Finance on a 4 / 1 days rhythm.
Two-year MSc built on three pillars. What I want to take home from it:
Goal. Turn a self-taught builder into a rigorous quant, ready to ship on a real ALM desk from day one, the apprenticeship at AFD.
Covers economic indicators, currencies, fixed income, interest rate risk and equities. Directly relevant to the ALM apprenticeship and the MSc.
Information systems, digital innovation, project management, quantitative methods.
Macro, micro, corporate finance, financial analysis, econometrics, applied statistics.
Programming fundamentals, algorithms, object-oriented design.
For two years I have been building what I could on my own: trading bots, backtest frameworks, automated research pipelines, a real estate investment model for my own portfolio. The outcome is a working stack. The limit is obvious too: I can ship, but I lack the quantitative depth to trust my own numbers.
The MSc Data & AI for Finance is the exact intersection I need. Mines Paris-PSL for the quantitative rigor (ML, risk modeling, ALM, Basel III/IV). Albert School for the business reflex and the access to the finance industry. Together they turn a self-taught operator into a serious quant profile.
Goal after the MSc: apprenticeship inside a trading desk, asset manager or quant fintech, then a career building the decision tools I already prototype today, only with the science behind them.
Dual background in economics and computer science. Self-study in quant finance and ML, Bloomberg BMC in progress.
From scraper to dashboard to live bot. Not demos: running systems I rely on myself.
Apprenticeship already secured at a public development bank. I arrive day one on an ALM desk, not in class.
Active investor, real money in ETFs and crypto, real estate deal underwriting on the side. Markets are my hobby, not my homework.
MSc questions, apprenticeship conversations, freelance briefs, or a quant problem over coffee. Pick the channel that fits.