Quantitative Trader - Boston - ALT Fund

Description

We are a prop-trading company that combines the agility of a startup with the resources of a high-performing fund.

Our team is focused on developing cutting-edge strategies, and working with us means not just advancing technology, but also being part of a team where ideas are valued, professional growth is encouraged, and every member has the opportunity to unlock their full potential.

We are looking for an experienced specialist with proven experience in Quantitative Research, including intraday trading.


What You'll Be Doing:
Designing and scaling strategies across various investment decision horizons — from seconds to several days
Generating ideas based on analysis of market microstructure, correlations, behavioral patterns, and inefficiencies
Proposing and improving tools for backtesting, cross-validation, risk management, and PnL analysis
Contributing to the development and fine-tuning of execution infrastructure, including order routing, slippage models, and latency sensitivity
Continuously adapting strategies to changes in market conditions and exchange infrastructure

Running fast iteration cycles:
generate → test → deploy → refine (with structured post-mortems)

Requirements


Experience:
2-5 years of experience at a prop trading firm or internal quant desk
Proven track record running live strategies with AUM > $1M or Sharpe > 2.0 on real accounts
Ownership of a complete alpha or tech stack — from idea generation to execution
Hands-on experience working with real-time data feeds, tick data, and low-latency infrastructure


Skills & Education:
Expertise in high-frequency or medium-frequency alpha generation
Solid understanding of market microstructure, latency arbitrage, and order book dynamics
Experience with real-time strategy automation and risk controls
Strong coding skills in C++ or Rust and Python, with the ability to write production-grade low-latency code
Proficiency in feature engineering and signal combination to maximize information ratio (IR)
Experience with backtesting frameworks — either in-house or open-source (e.g., bt, Zipline, or others)
Master's or PhD in a quantitative field such as Physics, Mathematics, Computer Science, or a related discipline

Languages:
Russian, English


Nice to have:
Understanding of options pricing models
Experience with machine learning, deep learning, or reinforcement learning (ML/DL/RL) techniques
Strong communication skills, with the ability to explain complex technical ideas to both technical and non-technical stakeholders

Benefits

Culture of Innovation:
An open, dynamic, and inclusive environment where your ideas matter

Flexibility & Impact:
Enjoy the freedom of a startup with the backing of a well-resourced fund

High Impact:
Work directly on projects that shape strategies and drive the fund's success
35 Days of Vacation - Plenty of time to rest and recharge
100% Paid Sick Leave - Recover without financial worries
Top-Tier Equipment - Choose the tools that suit you best (within budget)
Corporate Psychologist - Mental health support when you need it