Founding Quant/Trading Strategist - India

Equity Only | Pre-Seed Startup | India Only

About Us

We are building a next-generation AI-driven trading platform (Ai-CoPilot) that ingests massive streams of financial, alternative, and sentiment data and transforms them into actionable insights. Our mission is to combine robust data engineering pipelines with GenerativeAI and advanced ML models to democratize access to sophisticated trading strategies.

You’ll be the scientist who turns/tests our hypotheses/science into fundamental, risk-aware strategies.

The Role

Own the alpha discovery → validation → portfolio construction → live monitoring loop. You’ll design bias-resistant research, enforce model governance, and partner with AI/Backend to ship strategies that withstand market pressures (latency, costs, regime shifts). Expect hands-on Python and ruthless skepticism.

This role requires a DIY mindset with a willingness to educate the team about market strategies.

What You’ll Do

·       Alpha research & hypothesis testing: Generate/verify signals across price, volatility, fundamentals, and alt-data using rigorous statistics; separate luck from skill with robust tests and out-of-sample evidence.

·       Backtesting & validation: Build leak-proof pipelines (no look-ahead/survivorship), use purged/walk-forward/CPCV splits, and apply metrics like Deflated Sharpe to reduce backtest overfitting.

· Portfolio construction & risk: Translate signals into positions with constraints, drawdown controls, and stress tests across regimes; model slippage/fees/borrowing and reality-check edge after costs.

· Execution awareness: Define execution/SLO assumptions (latency budgets, order types, child-order logic) and partner with engineering on safe-guards/kill-switches for live strategies.

·       Model governance: Document assumptions, data lineage, andversioning; run champion-vs-challenger tests; practice independent validationconsistent with leading modelrisk management principles.

What We’re Looking For

·       8+ years in quant research/trading or equivalent track record shipping strategies.

·       Deep skills in Python(NumPy/Pandas/Numba/Statsmodels), time-series/stat inference, and ML formarkets.

·       Proven experience with bias-free backtesting, cross-validation for dependent data (e.g., CPCV), and cost/impact modeling.

·       Strong grasp of market microstructure and risk (exposures, drawdowns, regime shifts).

·       Startup DNA: skeptical, fast,documentation-minded, and comfortable owning results end-to-end.

Nice to Have

·       Publications or open research; familiaritywith SR 11-7-style model governance; experience collaborating withlow-latency engineering

First 90 Days (outcomes)

·       Ship a leak-proof research framework with CPCV/walk-forward, cost modeling, and standardized reports.

· Produce two vetted strategies that beat defined baselines after costs; document “model cards” and rollback criteria aligned with governance best practices.

·       Define live monitoring KPIs (edge decay, drift tests, latency/fill SLOs) and kill-switch thresholds consistent with algorithmic-trading control guidance.

Why Join

Be the architect of the alpha engine at day zero, with meaningful equity and a direct line from your research to user outcomes.