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Senior Quantitative Developer / Quant Trader

Rising Fund – Quantitative, Market-Neutral Digital Asset Hedge Fund | Global, Remote

About the Firm

Rising Fund is a quantitative, market-neutral digital asset hedge fund focused on systematic alpha generation across CeFi and DeFi markets. Our strategies span HFT, MFT, basis arbitrage, volatility carry, statistical arbitrage, and hedged DeFi yield, with an uncompromising focus on risk management, capital preservation, and scalable infrastructure.

We operate with an institutional mindset—production-grade systems, rigorous research, disciplined execution, and robust risk controls.

Role Overview

We are seeking a Senior Quantitative Developer / Quant Trader to design, implement, and operate low-latency, systematic trading strategies across centralized and decentralized crypto markets.

This role sits at the intersection of quantitative research, execution engineering, and risk-aware portfolio construction, working closely with the Fund Principal and investment leadership.

Key Responsibilities:

Strategy & Quantitative Research
  • Design, implement, and operate market-neutral quantitative strategies, including:
    • Perp–spot and cross-exchange basis
    • Funding rate arbitrage
    • Volatility carry and dispersion
    • Statistical arbitrage (pairs, baskets, cointegration)
    • Hedged DeFi yield strategies

  • Develop alpha signals using:
    • Price action and market microstructure
    • Order book imbalance and liquidity metrics
    • Funding rates, open interest, and positioning data
    • Regime detection and volatility filters

  • Analyze alpha decay, turnover, capacity, and scalability.
Execution & Trading Systems
  • Build and optimize low-latency execution systems in Go for live trading.

 

  • Design and maintain:
    • Order Management Systems (OMS)
    • Smart Order Routing (SOR)
    • Exchange-specific execution logic

  • Optimize execution quality through:
    • Slippage and market impact reduction
    • Queue positioning and order placement logic
    • Fee tier optimization and rebate capture

  • Implement robust risk-aware execution controls, including kill-switches and throttles.
CeFi & DeFi Trading
  • Trade and integrate across:
    • Spot, perpetuals, futures, and options
    • Major centralized exchanges and prime brokers

 

  • Design and manage DeFi strategies involving:
    • AMMs (Uniswap v3, Curve)
    • Lending protocols (Aave, Compound)
    • Perpetual DEXs

  • Incorporate on-chain execution costs, MEV awareness, and protocol-specific risks.
Backtesting & Simulation
  • Build and maintain tick-level backtesting frameworks in Python.
  • Accurately model:
    • Fees, funding, and rebates
    • Partial fills and order book dynamics
    • Latency, slippage, and exchange-specific rules

  • Perform Monte Carlo simulations, stress testing, and regime analysis.

Risk & Portfolio Management
  • Implement strategy-level and portfolio-level risk controls, including:
    • Exposure and leverage limits
    • Drawdown and tail-risk monitoring
    • Correlation and concentration analysis

Support volatility targeting, capital allocation, and portfolio optimization decisions.

Required Skills:

    • 3–8+ years in systematic trading, HFT, or quantitative development.
    • Proven experience running live trading strategies in production.
    • Strong understanding of PnL attribution, drawdowns, and failure modes.
      Coding & Systems Engineering
      • Go (Primary – Production & Execution)
        • Low-latency, concurrent system design
        • OMS, execution engines, and market data pipelines
        • Efficient memory management and profiling
        • Network programming (WebSocket / streaming APIs)
        • Lock-free or low-contention data structures

      • Python (Primary – Research & Simulation)
        • NumPy, pandas / polars for vectorized analysis
        • Backtesting and simulation framework development
        • Data cleaning, feature engineering, and research pipelines
      Quantitative Research & Modeling
      • Alpha signal development and validation:
        • Mean reversion, momentum, funding and basis signals
        • Volatility and regime-based strategies

      • Time-series analysis:
        • Stationarity testing
        • Cointegration
        • Signal decay and turnover analysis

      • Portfolio construction with transaction costs and constraints

      • Strong statistical validation and overfitting controls
      Market Microstructure & Execution
      • Order book dynamics and queue mechanics
      • Passive vs aggressive execution trade-offs
      • Slippage and impact modeling
      • Exchange-specific behaviors, fee structures, and liquidity profiles

      Mathematics & Statistics
      • Probability theory and linear algebra
      • Optimization techniques
      • Basic stochastic processes
      • Risk metrics (volatility, drawdown, CVaR)
      Infrastructure & Tooling
      • Linux
      • Docker and CI/CD workflows
      • Cloud basics (AWS / GCP)
      • Monitoring, logging, and alerting systems
      Experience Requirements
      • 3–8+ years in systematic trading, HFT, or quantitative development.
      • Proven experience running live trading strategies in production.
      • Strong understanding of PnL attribution, drawdowns, and failure modes.
      • Crypto markets experience (CeFi and/or DeFi) strongly preferred.