Senior Quantitative Trader

Algoedge Technology; Gurugram District; On-site; INR 17,029,000 - 28,382,000; Full time

Job summary

Algoedge Technology seeks a Senior Quantitative Researcher to design, test, and deploy systematic trading strategies in US markets. This role spans signal discovery to live deployment, with close collaboration with engineers, traders, and risk teams.

You will own the research lifecycle, validate strategies across equities, futures, and options, and mentor junior researchers while maintaining high standards and rigorous documentation.

Qualifications

• 5+ years in quantitative research or trading at a prop firm, hedge fund, market maker, or HFT/MFT.
• Proven live-strategy deployment with verifiable performance metrics.
• Hands-on experience with US market structure and latency-aware trading.

Responsibilities

• Design, test, and deploy systematic trading strategies across US equities, futures, and options.
• Build realistic backtesting/ simulation frameworks accounting for latency, fees, and slippage.
• Analyze tick data and order books to find signals and improve execution quality.
• Collaborate with engineers to productionize strategies in low-latency environments.
• Monitor live performance, perform post-trade analysis, and iterate based on data.
• Define risk parameters, position limits, and kill-switch logic with risk team.

Skills

Quantitative research

Backtesting

Signal discovery

Python

ML basics

C++

Low-latency systems

US markets knowledge

Education

MS/PhD in Math/Stats/CS/Engineering

Tools

kdb+/q

Parquet

FIX protocol

ITCH/OUCH/PITCH data feeds

Job description

Senior Quantitative Trader
US Markets, HFT | MFT

About the Role

We are looking for a Senior Quantitative Researcher to design, test, and deploy systematic trading
strategies in US markets. This role suits someone who has taken strategies from idea to production,
understands what separates a good backtest from a strategy that survives live, and is comfortable
working close to the metal in a low-latency, high-frequency environment.
You will own the full research lifecycle, from signal discovery to live deployment and monitoring, working
alongside engineers, traders, and risk.

What You Will Do

• Research, develop, and validate systematic strategies (market making, statistical arbitrage, short-horizon alpha, or related approaches) across US equities, futures, and/or options.
• Build and maintain realistic simulation and backtesting frameworks that account for queue position, latency, fees, slippage, and market impact.
• Analyze high-frequency tick and order book data to find predictive signals and improve execution quality.
• Work with the infrastructure and engineering teams to take strategies into production, including latency-sensitive components, co-location setups, and exchange connectivity.
• Monitor live performance and run post-trade analysis (P&L attribution, adverse selection, fill rates, slippage, drawdown), then iterate based on the data.
• Define and enforce risk parameters, position limits, and kill-switch logic in coordination with the risk team.
• Document research findings clearly and present results to the team and senior stakeholders.
• Mentor junior researchers and raise the team's research standards.

What We're Looking For

• 5+ years of experience in quantitative research or trading at a prop firm, hedge fund, market maker, or HFT/MFT shop.
• A proven record of building and deploying strategies that ran live, not just in backtests, with verifiable performance (Sharpe, drawdown, capacity, hit rate).
• Hands‑on experience with US markets, including their structure (NMS, ATS/dark pools, exchange fee tiers, order types, auction mechanics).

Technical Skills

Strong grounding in market microstructure, order book dynamics, and execution.
Strong statistical and ML foundations: time-series analysis, signal processing, regularization, and an awareness of overfitting and data-snooping risks.
Proficiency in Python (NumPy, pandas, scikit-learn, etc.) for research, plus working knowledge of C++ or another low-latency language.
Comfort working in an HFT infrastructure environment: tick-level data, FIX/binary exchange protocols, market data feeds (e.g., ITCH, OUCH, PITCH), co-location, and latency measurement and optimization.
Experience handling large datasets (tick data, L2/L3 order books) with tools such as kdb+/q, Parquet, or similar.
Mindset
Ownership and the ability to work independently with minimal oversight.
Intellectual honesty about what works, what doesn't, and why.
Clear communication of complex ideas to both technical and non-technical audiences.
Nice to Have
Experience with options market making or volatility strategies.
Familiarity with FPGA or kernel-bypass technologies.
Advanced degree (MS/PhD) in Mathematics, Statistics, Physics, Computer Science, Engineering, or a related quantitative field.
Experience across multiple asset classes or global venues.

Why Join Us

Real ownership of research and strategies, with a direct line from your work to live P&L.
A performance-driven culture with [compensation structure: base + performance bonus / profit share].
Access to high-quality data, modern infrastructure, and low-latency connectivity.
A clear growth path to lead research or run your own book.