Case studies, not a project gallery

Most quant systems have a gap between trading idea and execution: insufficient data, backtests without real costs, strategies without market regime awareness and non-reproducible results.

Data quality in 6 layers, execution costs (fee + slippage + 1-bar delay), no look-ahead bias, full reproducibility and modular architecture.

The pipeline was designed from hypothesis to report: data → validation → strategy → backtest → walk-forward → Monte Carlo → dashboard.

Three-layer architecture: Browser Dashboard / FastAPI / Research Library on Parquet Data Store. 8 strategy families in frozen dataclasses, vectorized numpy/pandas backtesting.

Trading decisions are grounded in quantitative evidence. Walk-forward and Monte Carlo reveal the difference between a real strategy and a curve-fitted one.

CAGR, Sharpe, Sortino, Calmar, Max Drawdown, Win Rate, Profit Factor — all computed with real execution costs.

Trading logic without test architecture, risk control and a live optimization loop.

Data quality, drawdown, 24/7 execution, error monitoring, liquidation guardrails and backtest/live mismatch.

The strategy was decomposed into hypothesis, risk metrics, execution rules and review cadence.

Backtest module, risk layer, execution logic and monitoring dashboard.

Decisions about continuing, stopping or improving the strategy became clearer.

Focus on drawdown, win/loss distribution, exposure and execution errors.

Practice operations and patient experience from booking to intake, messaging, settlement and daily reporting needed one connected flow.

Patient trust, simple experience, OTP, doctor/secretary/patient roles, precise follow-up and usable data flow.

The product was designed as a coordination system between patient, clinic and operational decisions.

Workflow, admin panel, data capture and follow-up paths.

Follow-up and status visibility improved, reducing abandoned opportunities.

Response time, follow-up rate, process completion and data quality.

The clinic needed a multi-role system for scheduling, records, finance, inventory, loyalty and intelligent analytics.

Small team, limited time, simple capture, fast reporting, reducing no-show and connecting finance/care operations.

The CRM needed to simplify team behavior, not create new administrative load.

Pipeline, lead status, reminders, reporting and follow-up ownership.

Sales opportunities became more visible and follow-ups more controllable.

No-show under 5%, intake-to-visit cycle under 8 minutes, patient return rate above 35%, lead aging and pipeline status.

A multi-engine signal platform needed to support fast delivery, decision quality and scalable product operations at the same time.

Product simplicity, simultaneous web/Telegram/alert delivery, subscription model, admin operations, behavioral data and fast delivery.

The design had to make the product usable while enabling learning from users.

Product flow, data points, control panel and staged improvement.

Product decisions were supported by better data and observation.

Activation, retention, completion and friction points.