Quantitative Portfolio Manager

About Par Trading

Par Trading is a Hong Kong–based proprietary trading firm. We trade our own capital across traditional financial markets and digital-asset markets.

We are building a lean, high-performing quantitative trading team. The firm provides capital, unified trading and research infrastructure and an independent risk-management framework; portfolio managers have full autonomy over strategy research, portfolio construction and capital use within a defined risk framework.

The team runs on a small-pod model. Each Quantitative Portfolio Manager owns an independent strategy portfolio and progressively adds quantitative researchers and trader / execution resources as the strategies require.

The role

We are looking for 2–3 Quantitative Portfolio Managers to build, run and continuously develop independent systematic trading portfolios.

This is an investment role with clear P&L, risk and team responsibility. You set the research and trading direction, establish sustainable sources of alpha, construct and manage the strategy portfolio, and keep improving risk-adjusted return on capital in the live market.

As strategies and live performance are validated, the firm progressively expands capital allocation, risk budget and team resources.

Key responsibilities

Strategy and research direction: set the pod’s core research areas and trading direction; keep finding, validating and developing alpha sources with economic logic and durability.
Portfolio construction: integrate signals and strategies into a complete portfolio; manage exposure, correlation, concentration, liquidity, capacity and portfolio-level return characteristics.
Capital and risk management: own the pod’s use of capital and risk within the firm’s overall framework; adjust risk allocation dynamically on expected return, strategy quality, live performance and market conditions.
P&L ownership: take direct responsibility for the pod’s live results; continuously attribute and review returns, drawdowns, exposures and live-vs-expected gaps.
Strategy lifecycle management: keep evaluating strategy effectiveness; separate normal statistical variance, regime change, execution slippage and alpha decay, and decide to scale, adjust, de-risk or retire accordingly.
Research leadership: set systematic, rigorous research standards; guide quantitative researchers through data research, signal development, modeling, backtest validation and strategy iteration.
Execution oversight: supervise live execution — transaction costs, slippage, liquidity use, market impact and automated-trading quality.
Team leadership: hire, manage and develop the pod’s researchers and traders as strategies grow; build a high-standard, high-autonomy, results-driven culture.
Infrastructure collaboration: work with engineering and risk to keep improving data, research, backtesting, execution, monitoring and risk-management infrastructure.
Market expansion: progressively extend tradable markets, products, horizons and capital scale as capability and opportunity allow.

What we require

Mature quantitative, systematic or proprietary trading experience with a verifiable real-capital track record;
Independent ownership of a strategy portfolio, risk book or trading mandate with explicit P&L responsibility;
The ability to clearly explain your strategies’ alpha sources, risk sources, capacity, market conditions and potential failure modes;
Full strategy lifecycle experience: research, backtesting, production, live trading, scaling, drawdown management and strategy retirement;
Deep understanding of portfolio construction, risk management, transaction costs, execution and market microstructure;
The ability to separate statistical correlation from economically grounded, durable opportunities, with strong sensitivity to overfitting, crowding and regime dependency;
Sound capital-allocation judgment: clear trade-offs across strategies and opportunities on risk-adjusted return;
Willingness to revise views and risk promptly when markets or models deviate from expectation, rather than relying mechanically on historical models;
Experience or clear ability to lead a small quant research / trading team;
High professional integrity, risk awareness and ownership of trading outcomes;
The ability to operate in 24/7, cross-venue, highly dynamic digital-asset markets and quickly understand perpetual futures, funding, cross-venue liquidity and digital-asset microstructure. Crypto experience is preferred but not required.

Preferred strategy backgrounds

We are open on strategy type, with particular interest in: CTA / futures / trend / momentum · statistical arbitrage · systematic equities · order flow / market microstructure · intraday / short-horizon systematic trading · market making / liquidity provision · volatility / options · systematic macro · hybrid systematic + discretionary strategies

We do not judge candidates by a single strategy label. We care most about: explainable alpha, validated live ability, strict risk discipline, and the ability to scale.

Compensation and capital allocation

We offer competitive fixed compensation and performance incentives tied directly to real investment results.

Given the continuous trading, rapid strategy iteration and fast capital turnover of crypto markets, portfolio managers’ performance and capital allocation are formally reviewed on a quarterly basis. Incentives are based primarily on the risk-adjusted P&L of the portfolio you run, taking into account drawdown, capital efficiency, risk discipline, strategy capacity and return stability.

For portfolio managers who keep producing verifiable alpha with sound risk management, the firm expands capital allocation, risk budget and team resources dynamically — without waiting for an annual cycle.

The performance mechanism uses a rolling high-water mark and a deferral arrangement, providing frequent positive incentives while keeping portfolio managers and the firm aligned on risk and return across cycles.

Location

Hong Kong. Shenzhen serves as a transitional office initially; after formal onboarding, the Hong Kong office is the primary place of work and trading.

How to apply

Please send your CV to careers@par.ai.

Through the process we hope to understand your experience in:

the markets, strategies and portfolios you have run;
historical capital / risk budget and strategy capacity;
live return, risk and drawdown characteristics;
alpha sources and principal risk factors;
how you handled major drawdowns or strategy deterioration;
how strategies are expected to change with more capital, and how you scale;
team management and research process.

Please do not share any confidential, proprietary strategy, code or sensitive data belonging to a current or former employer.