Quant Researcher - Distinguished Founders - Ground Floor

CareerXperts Technologies Private Limited; Hyderabad; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

CareerXperts Technologies Private Limited is seeking a Quant Researcher to design, validate, and deploy production-grade research pipelines that transform raw data into robust signals. You will work closely with engineering and trading teams to ensure models are production-ready and well-documented.

Responsibilities include rigorous validation, stress testing, and defining standardized handoffs for real-time risk and execution telemetry.

Qualifications

• Strong background in quantitative research and signal generation.
• Experience building reliable Python data pipelines.
• Familiarity with backtesting, risk metrics, and live trading integration.

Responsibilities

• Architect and ship end-to-end, production-ready research pipeline.
• Pressure-test hypotheses with out-of-sample validation, stress testing, regime-shift analysis.
• Define handoff standards: signal architecture, real-time risk, and execution telemetry.
• Advocate lean processes; ensure research translates to production.

Skills

Quantitative research

Python

Backtesting

Data pipelines

Signal generation

Tools

Python

Pandas

Backtesting frameworks

Job description

Generate, validate, and improve research that survives real markets—and translates cleanly into production.

Most alpha dies the moment it meets a real market. Yours won’t.

A quantitative proprietary trading firm operating across global markets is building a flat, high-agency team, and wants a Quant Researcher who treats leakage, overfitting, and bias as personal enemies. You’ll generate and validate systematic ideas, build reliable Python pipelines on real data, and work shoulder-to-shoulder with engineering and trading to make the path to production disciplined and explicit.

01 Architect and ship an end-to-end, production-ready research pipeline that seamlessly transforms raw data into reproducible signal generation and fully documented models.

02 Pressure-test core trading hypotheses through rigorous out-of-sample validation, failure-mode stress testing, and exhaustive regime-shift analysis to establish actionable alpha limits.

03 Define the quantitative handoff standard for the organization—synchronizing signal architecture, real-time risk metrics, and execution telemetry directly into engineering workflows.

No bureaucracy. No hiding behind process. Just research that survives and ships.

Microstructure or execution-aware modeling instincts? Even better.