AP Executive are working with a client who are building institutional-grade crypto intelligence terminal. They're creating a unified platform that transforms blockchain data into actionable insights at scale. They're building the data layer and infrastructure that makes deep on-chain analysis accessible without specialised expertise.
The Role
We're looking for a quantitative researcher to design the analytical frameworks that power our platform. This isn't about implementing someone else's models. This is about defining what "smart money" means, creating signals, and building metrics that don't exist yet.
The problems are legitimately interesting :
- How do you score wallet behavior in a pseudonymous environment?
- What signals distinguish accumulation from manipulation?
- How do you measure capital flows across fragmented liquidity?
- What blockchain-native metrics predict protocol success?
You'll work closely with our Senior Blockchain Data Engineer to turn research into production systems. This is a deeply collaborative role - you'll need to understand what's feasible with blockchain data infrastructure and help shape how we architect our data layer to support sophisticated analysis.
What You'll Do
Design quantitative frameworks for analysing onchain behavior (wallet scoring, entity classification, flow analysis)Create market microstructure indicators that work across CEXs, DEXs, and L2sBuild risk and anomaly detection systems for 300M+ walletsDevelop blockchain-native metrics (realized cap, holder behavior, network effects)Research signal validity and backtest against historical dataCollaborate with data engineering to architect systems that can compute your models at scaleTurn research into production systems that run automaticallyThis role is part research, part engineering, part product. You'll have significant autonomy over what you build.
This role is right for you if :
You understand blockchain data from first principles, what it measures and what it doesn'tYou can design metrics that work across different chain architecturesYou think about supply dynamics, holder behaviour, and flow analysisYou care about creating interpretable, actionable metrics, not just correlationsYou want your research to define how people understand on-chain activityYou have strong quantitative foundations (statistics, probability, modelling)You've built quantitative models that were used in productionYou're comfortable working with messy, incomplete dataYou can collaborate effectively with engineers and other members to ship your workYou can explain complex ideas clearly to non-technical stakeholdersRequired Qualifications
Education :
PhD or Master's degree in Mathematics, Statistics, Physics, Computer Science, Economics, Financial Engineering, or related quantitative fieldPreferred : Oxford, Cambridge, MIT, Stanford, Harvard, Princeton, Yale, ETH Zurich, Imperial College London.Exceptional undergraduate candidates from these institutions with demonstrated research excellence will be consideredExperience :
Minimum 3-5 years building and deploying quantitative models in production environmentsProven track record of models that generated measurable impact (P&L, predictive accuracy, operational improvements)Experience with large-scale data analysis and statistical modellingDemonstrated ability to take research from conception through production deploymentTechnical Requirements :
Expert-level proficiency in Python or relevant coding languageStrong foundation in probability theory, statistical inference, and time series analysisExperience with back testing frameworks and validation methodologiesComfortable writing production-quality code, not just research scriptsSQL and data manipulation at scaleDomain Knowledge :
Deep understanding of market microstructure and trading dynamicsExperience analysing financial time series and behavioural patternsFamiliarity with quantitative finance concepts (risk metrics, portfolio theory, signal processing)Blockchain / crypto experience is valuable but not required if you have strong foundations and can learn quicklyCandidate Profile - What Distinguishes Top Performers
We're looking for researchers who have consistently operated at the highest level. Successful candidates typically have :
Demonstrated Excellence :
Publications, patents, or proprietary models that were recognized as significant contributionsTrack record of solving problems others couldn't solveModels or research that became reference points in their fieldRecognition from peers as being at the top of their domainProduction Impact :
Built systems that processed billions of data points reliablyModels that were trusted for high-stakes decisions (trading, risk management, allocation)Research that directly generated revenue or competitive advantageExperience shipping research into production, not just writing papersIntellectual Rigor :
Ability to design novel approaches from first principlesStrong intuition for what will work before testingClear thinking about causation vs. correlationComfort with mathematical complexity when necessary, pragmatism when it's notCollaborative Capability :
Experience working with engineering teams to productionize researchAbility to explain complex concepts to non-technical stakeholdersTrack record of mentoring or leading research effortsComfort taking feedback and iteratingWhat Makes This Role Different
This is a research role with unusual scope and impact. You'll be designing analytical frameworks that define how institutional capital understands on-chain activity.
The opportunity :
Design entirely new metrics and analytical primitives, not incremental improvements to existing modelsFull access to multi-chain infrastructure, compute resources, and engineering support to productionize your workYour frameworks will be used by institutional investors making real allocation decisionsDirect ownership of your research domain with minimal oversightWork that gets attributed to you and builds your professional reputationTo apply please send your CV to Don Fletcher via or via whatsapp on +44 7817 258331
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