Monad
Quantitative Researcher
RemoteFull-timeGlobal
š Midš Remote
RemoteRemote work position available
Job Description
[AI-summarized by JobStash]
You will develop predictive models for transaction dependencies, user behavior, and network behavior in the blockchain space. You will prototype and evaluate multiple modeling approaches for open-ended problems, then implement production-grade solutions and take end-to-end ownership of prediction pipelines. You will apply techniques such as linear regression, decision trees, and neural networks and use numpy and pandas to build robust, performant systems. Experience in high-frequency trading or environments where predictive analytics directly impacted the bottom line is a plus.
Requirements
- āAt least 3 years of experience building predictive models, preferably at a high-frequency trading firm.
- āExcellent knowledge of predictive modeling techniques including linear regression, decision trees, and neural nets.
- āProficiency with numpy and pandas.
- āProven track record building significant projects from scratch.
- āCreative, self-motivated, and independent.
- āBonus: crypto-native.
Responsibilities
- āDevelop predictive models for transaction dependency, user behavior, and network behavior.
- āPrototype and evaluate multiple modeling approaches for open-ended problems.
- āImplement production-grade prediction solutions and own end-to-end production pipelines.
- āApply predictive modeling techniques including linear regression, decision tree, and neural network.
Tech Stack
high-frequency tradingpandasnetwork analysisdecision treePrototypingtransaction dependencynetwork behaviorlinear regressionmachine learningNumPy