AlgoQuant Asset Management — a multi-strategy digital asset manager founded in 2018, allocating capital across 25+ internal and external quantitative trading pods, serving family offices and institutional investors globally across UAE, USA, UK, EU, and Asia — is hiring a DeFi Quant Researcher to design, test, and deploy systematic strategies native to decentralised markets. This deeply technical, research-first role generates alpha from DeFi-specific signals — liquidity dynamics, protocol incentive structures, on-chain order flow, and cross-protocol arbitrage — and requires a researcher who understands on-chain mechanics from first principles, not just as a theme, but as a genuine source of exploitable, measurable edge. You will own your research end-to-end.
About AlgoQuant Asset Management — Institutional DeFi Alpha
Company: AlgoQuant Asset Management — a multi-strategy digital asset manager combining trading edge with strong governance and advanced technology across 25+ internal and external quantitative trading pods
Founded: 2018 — evolved into an institutional platform serving family offices and institutional investors globally across UAE, USA, UK, EU, and Asia
DeFi Research Role: Research-first, end-to-end ownership — working directly with portfolio managers and engineers who move at your pace, with full autonomy over your DeFi systematic research programme
Timezone: Asia or US timezone strongly preferred — ensuring coverage of key DeFi market hours and fast iteration on live strategy performance
Why This DeFi Quant Researcher Role Stands Out
End-to-End Research Ownership: You own the full research lifecycle — from alpha signal identification through backtest validation, live deployment, and performance iteration — with direct access to portfolio managers and engineers who move at your speed
Genuine DeFi Edge Focus: AlgoQuant generates alpha from structural DeFi inefficiencies — AMM liquidity dynamics, MEV, protocol incentives, on-chain order flow — not macro themes or narrative-driven positions
Institutional Platform at Scale: 25+ quant pods, institutional governance, family office and institutional LP base — a credible, well-resourced institutional framework for deploying serious DeFi research into live capital
Global Presence: UAE, USA, UK, EU, Asia — contributing to one of the most internationally distributed quantitative digital asset management platforms in operation
Position Overview
This DeFi Quant Researcher at AlgoQuant Asset Management designs, tests, and deploys systematic trading strategies across DeFi protocols — AMMs, lending markets, perpetuals, yield vaults, and cross-chain venues — building and validating alpha signals from on-chain data including liquidity flows, wallet behaviour, MEV dynamics, funding rates, and protocol-level incentives. The role analyses smart contract mechanics and tokenomics to identify structural edges, runs rigorous backtests and simulations accounting for on-chain-specific constraints including gas costs, slippage, block timing, and data availability, collaborates with engineers to deploy strategies into live capital, monitors live performance and iterates rapidly on results, and contributes to shared research infrastructure, on-chain data pipelines, and analytical tooling — with full research ownership from first principles through live deployment.
Why This Role Matters: As DeFi Quant Researcher at AlgoQuant, you operate in one of the most technically demanding and genuinely alpha-rich environments in quantitative finance — on-chain markets where smart contract mechanics, AMM curve mathematics, MEV dynamics, and protocol incentive structures create structural inefficiencies that are exploitable only by researchers who understand the market from first principles, not from a high-level DeFi overview. When your on-chain signal correctly identifies a persistent funding rate dislocation across perpetual protocols that a surface-level scan would miss, your backtest properly accounts for gas cost variability and block-timing constraints that invalidate naive strategy simulations, or your smart contract analysis surfaces a tokenomics structure that creates predictable on-chain order flow for three to six months before the market corrects it — that is what genuine DeFi quantitative research looks like. AlgoQuant is building the platform to deploy it.
Responsibilities
DeFi Strategy Research, Signal Development & Alpha Generation
- Research and develop systematic trading strategies across DeFi protocols — AMMs, lending markets, perpetuals, yield vaults, and cross-chain venues — identifying exploitable structural inefficiencies from first-principles analysis of on-chain market mechanics
- Build and validate alpha signals from on-chain data — liquidity flows, wallet behaviour, MEV dynamics, funding rates, and protocol-level incentive structures — using The Graph, Dune Analytics, raw node data, and proprietary pipeline tooling
- Analyse smart contract mechanics and tokenomics to identify structural edges — going beyond surface-level protocol documentation to understand the precise mathematical and incentive structures that create measurable, exploitable on-chain price dynamics
- Generate alpha from DeFi-specific signal categories: AMM curve liquidity dynamics, cross-protocol arbitrage, protocol incentive farming opportunities, on-chain order flow prediction, and MEV-adjacent positioning strategies
Backtesting, Simulation & On-Chain Constraint Modelling
- Run rigorous backtests and simulations with obsessive attention to on-chain-specific validity issues — gas cost variability, slippage modelling, block timing constraints, data availability lag, and the distinction between tick data and on-chain settlement reality
- Apply statistical rigour throughout the research process — paranoid identification of lookahead bias, data leakage, and overfitting risks that are uniquely prevalent in on-chain research due to the public availability of historical blockchain data
- Stress-test strategy edge against realistic on-chain friction — confirming that identified alpha survives transaction costs, MEV exposure, gas competition, and capacity constraints before deployment into live capital
Live Deployment, Performance Monitoring & Research Infrastructure
- Collaborate with AlgoQuant’s engineers to deploy validated strategies into live capital — providing the research specifications, signal definitions, and performance benchmarks needed for production implementation
- Monitor live strategy performance and iterate rapidly on results — applying fast feedback loops between live performance data and research refinement to maintain edge as on-chain market dynamics evolve
- Contribute to shared research infrastructure, on-chain data pipelines, and analytical tooling — improving the speed, reliability, and capability of AlgoQuant’s DeFi research platform for the broader quant research team
What AlgoQuant Is Looking For
Essential Profile
- Strong mathematical or scientific background — top-decile graduates or postgraduates in mathematics, physics, computer science, or a quantitatively equivalent discipline
- Deep, hands-on familiarity with DeFi protocols and on-chain market structure — meaningful time actually operating in these markets, not just reading about them from the outside
- Experience working with on-chain data sources — The Graph, Dune Analytics, raw node data — and building research pipelines from them in Python
- Strong Python programming — production-quality, well-structured code applied to on-chain data extraction, signal development, backtesting, and research infrastructure
- Statistical rigour — a paranoid, disciplined eye for lookahead bias, data leakage, and overfitting in on-chain research contexts
- Self-directed and high-agency — comfortable owning research end-to-end without hand-holding, and driving progress in ambiguous problem spaces with limited guidance
Advantageous Skills
- Solidity familiarity or smart contract auditing experience — enabling deeper protocol-level analysis and edge identification from contract-level mechanics
- Asia or US timezone — strongly preferred to ensure coverage of key DeFi market hours and real-time iteration on live strategy performance
- Cross-chain experience — understanding of bridge mechanics, chain-specific AMM implementations, and cross-venue arbitrage dynamics
- MEV research background — specific understanding of maximal extractable value mechanics, searcher strategies, and MEV-adjacent market structure effects
About AlgoQuant Asset Management — Institutional DeFi Quant at Scale
AlgoQuant Asset Management was founded in 2018 and has evolved into a leading institutional multi-strategy digital asset manager — allocating capital across 25+ internal and external quantitative trading pods, combining rigorous trading edge with strong governance and advanced technology infrastructure. Serving family offices and institutional investors globally across UAE, USA, UK, EU, and Asia, AlgoQuant’s DeFi Quant Researcher role represents the firm’s commitment to deploying serious research-first systematic strategies in decentralised markets — not marketing narratives, but genuine, measurable, structurally grounded on-chain alpha. If you are a researcher who has spent real time in DeFi markets, understands on-chain mechanics from first principles, and has the Python depth and statistical discipline to convert that understanding into deployable systematic strategies — AlgoQuant is building the institutional platform to scale what you find.
Career Excellence: Design and deploy DeFi systematic strategies — AMM, MEV, on-chain data, Python, Solidity at AlgoQuant’s 25-pod institutional platform, UAE.
Who Should Apply?
- DeFi Protocol Researchers — First-Principles Thinkers: Who have spent meaningful time in on-chain markets, understand AMM curve mathematics, liquidity dynamics, and protocol incentive mechanics from the ground up — not from a high-level summary
- On-Chain Systematic Strategy Developers — Python + Data: With experience building on-chain data pipelines using Dune, The Graph, or raw node data — and constructing, backtesting, and validating systematic DeFi trading strategies
- MEV & AMM Mechanics Analysts: Who understand maximal extractable value dynamics, AMM arbitrage, and the structural consequences of liquidity pool mechanics for systematic on-chain trading strategy design
- Quantitative Finance Graduates — DeFi Specialists: Top-decile mathematics, physics, or computer science graduates with genuine, demonstrable on-chain market experience — either through live trading, open-source DeFi research, or attributable systematic strategy deployment
- UAE-Eligible DeFi Researchers — Asia/US Timezone: Based in or accessible from UAE, operating in Asia or US timezone — seeking a research-first, end-to-end ownership role at an institutional multi-strategy digital asset manager with 25+ quant pods
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