Quant Developer
根据你的背景和兴趣,你将加入我们的库存战略团队之一。我们的策略涵盖贷款和信用策划,跨链收益汇集,结构化产品,RWAs 等。团队拥有整个战略生命周期:研究和协议 Due Diligence,策略设计和后测,配置和重新平衡引擎,在链上执行和优化,以及24小时监控现场位置。你拥有端到端的战略,并负责其性能,安全和运行时间。你将要做什么?·设计和船舶保险策略:从论文和设计文件中通过实施,模拟,部署和实体操作采取战略;RWA,利贷款,收益总结,跨协议分配,永久性,预测市场以及我们尚未构建的新产品类型。·优化策略:信号研究,执行优化,在代币和链之间实现气体意识重平衡,流动性和持续管理。·运行协议和资产 Due Diligence: 评估新协议,担保资产和链条用于战略中纳入可偿金机制,预言设计,赎回路径,流动性深度等。· 自己的风险参数:供应限制,LLTV 设置,集中限量,基于 VaR 的暴露模型以及在条件恶化时抽取位置的自动降低风险逻辑。· 将新的协议和链条集成起来:为贷款市场构建并验证适配器,DEX 汇总器和桥梁;对叉链模拟进行策略行为验证。在资本触摸之前监测:· 你所构建的是什么:扩大我们的风险监测和警报系统,定义某人关注的条件,并参与你拥有的战略的通话轮换。· 支持发射和客户:与增长,资本市场以及新库存和策略发射的客户团队合作。要求 · 在生产中运行的量化系统建设的历史记录算法交易,投资组合优化,市场制造或在贸易公司,资产管理者,金融科技或加密货币公司的风险系统。这往往是28年的经验,但我们重视了你多年来建立的东西在简历上。· 你写出你的战略背后的代码。
查看英文原文
This is not a research seat where models get handed off to someone else's pipeline — you design the strategy, write the code, deploy it, and own it in production. If you want your models allocating real capital onchain within weeks of joining, read on.
Depending on your background and interests, you'll join one of our vault strategy teams. Our strategies span lending and credit curation, cross-chain yield aggregation, structured products, RWAs, and more. Teams own the full strategy lifecycle: research and protocol due diligence, strategy design and backtesting, allocation and rebalancing engines, onchain execution and optimization, and 24/7 monitoring of live positions. You own strategies end-to-end and are accountable for their performance, safety, and uptime.
What you'll do;
- Design and ship vault strategies: take a strategy from thesis and design doc through implementation, simulation, deployment, and live operation — RWAs, leveraged lending, yield aggregation, cross-protocol allocation, perpetuals, prediction markets, and new product types we haven't built yet.
- Optimize strategies: signals research, execution optimization, gas-aware rebalancing across tokens and chains, liquidity and duration management.
- Run protocol and asset due diligence: evaluate new protocols, collateral assets, and chains for inclusion in strategies — solvency mechanics, oracle design, redemption paths, liquidity depth, and more.
- Own risk parameters: supply caps, LLTV settings, concentration limits, VaR-based exposure models, and automated de-risking logic that pulls positions when conditions deteriorate.
- Integrate new protocols and chains: build and validate adapters for lending markets, DEX aggregators, and bridges; verify strategy behavior against forked-chain simulation before capital touches it.
- Monitor what you build: extend our risk-monitoring and alerting systems, define the conditions that page someone, and participate in the on-call rotation for the strategies you own.
- Support launches and clients: partner with growth, capital markets, and client teams on new vault and strategy launches.
Requirements
- A track record of building quantitative systems that run in production — algorithmic trading, portfolio optimization, market making, or risk systems at a trading firm, asset manager, fintech, or crypto-native company. This is often 2–8 years of experience, but we weight what you've built over years on a résumé.
- You write the code behind your strategies. Strong Python and solid software-engineering fundamentals: testing, code review, and the judgment to build durable abstractions rather than one-off scripts. This is a hands-on, quantitative role — not a discretionary trading seat.
- Applied quantitative skills: optimization, statistics, and simulation, and the instinct to validate models against real data before trusting them.
- Comfort with data infrastructure: SQL and experience building or consuming data pipelines.
- Production ownership: you've debugged live systems under pressure and understand that a strategy managing other people's money has to be correct, monitored, and recoverable.
- Clear technical communication.
Bonus points
- Hands-on DeFi experience: lending protocols, ERC-4626 vaults, AMMs, or oracle systems — as a builder or a sophisticated user.
- Solidity / EVM literacy: reading protocol contracts, forked-chain simulation (anvil), or writing adapters; non-EVM experience (e.g., Solana) also valued.
- On-chain operational experience: multisig workflows, transaction submission and signing infrastructure, bridging.
- TypeScript, and familiarity with a modern data stack (e.g., BigQuery, Dagster, Hex, GCP/Kubernetes).
- Experience with risk modeling for volatile or thinly-traded assets: VaR, liquidation modeling, stress testing.
Who thrives here;
- Wants end-to-end ownership — research, code, deployment, and the pager — not a hand-off between research and engineering.
- Comfortable that crypto markets don't close. Strategy owners take on-call seriously, and the occasional market-event night is part of the job; we staff and rotate to keep it sustainable.
- Operates well in ambiguity: can take "we should have a strategy for X" and return a scoped design, not a list of questions — and is comfortable in a fast-moving space where priorities and team structure evolve.
- Holds a genuine risk view and voices it — including "we shouldn't do this" when the analysis says so.
- Pragmatic about shipping: balances rigor against client timelines without cutting corners on safety.
- Naturally curious about digital assets and DeFi. Deep crypto experience is not required — curiosity and strong quant fundamentals are.
Benefits
- Remote first — work from anywhere in the US & Canada
- Regular in-person company retreats and cross-country "office visit" perk
- 100% paid medical, dental, and vision premiums for employees
- $1,000 WFH stipend
- Monthly reimbursement for home internet, phone, and cellular data
- Unlimited vacation
- 100% paid parental leave of 12 weeks
- Fertility benefits
- Opportunity for incentive compensation
Please note at this time our hiring is reserved for potential employees who are able to work within the contiguous United States and Canada. Should you need alternative accommodations, please note that in your application.
The national pay range for this role is $175,000 – $200,000 base plus additional On Target Earnings potential by level and equity in the company. Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits, and other reward opportunities we provide. Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.
Originally posted on Himalayas