Engineer

This is a remote opportunity for one of our client.

Roles and Responsibilities :

• Forecasting Engine Ownership: Build and maintain production forecasting models (seasonal baselines, regularized regression, LightGBM panel models with conformal calibration, and time-series foundation models) behind a unified interface.
• Validation & Rigor: Own walk-forward backtesting, point-in-time (as-of) data correctness, leakage detection, prediction intervals, and hierarchical reconciliation (lane to corridor to index).
• Signal Validation & Graph Integration: Run pre-registered signal-validation loops (false-discovery-rate control, bootstrap/placebo checks) and evaluate graph-derived features (centrality, capacity) through the backtest fabric.
• AI-Native Engineering: Build and ship production code daily using AI coding agents (Claude Code, Cursor), enforcing CI/CD guardrails, rigorous testing, experiment tracking (MLflow), and clean Git workflows.

Job Requirements :

• Experience: 5–8+ years in production time-series/panel forecasting (logistics, freight, or finance background preferred).
• Tech Stack: Python, SQL, Pandas/Polars, LightGBM, MLflow, Docker, and APIs.
• Statistical Mastery: Walk-forward validation, backtesting, calibration, and hypothesis testing.
• AI-Native Workflow: Fluent in orchestrating AI coding agents and reviewing AI-generated code.
• Exclusions: No LangChain, RAG, prompt engineering, or generic LLM wrapper profiles.