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web3 Data Science Lead

Giza
RemoteRemotevia BlockJobsPosted 5/29/2023
full timemachine learningdata scienceweb3 & blockchain technologiespythoncross-functional collaborationdocumentation & communicationproblem-solving & analytical skills
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About the role

Responsibilities: - Develop, implement, and maintain machine learning models and algorithms to address complex business problems and enhance our product offerings. - Collaborate with cross-functional teams to identify, scope, and prioritize machine learning use cases and integrations within the product portfolio. - Lead the end-to-end development and deployment of ML solutions, from data collection and preprocessing to model training, evaluation, and optimization. - Leverage knowledge of Web3, Ethereum, and Rollups technologies to design and implement ML models for decentralized systems and applications. - Develop and maintain documentation, including technical specifications, user guides, and best practices, to support internal and external users. - Foster a culture of collaboration, communication, and continuous improvement within the team and across the organization, working closely with stakeholders from different areas. - Act as the subject matter expert for machine learning and data science, providing guidance and mentorship to team members and stakeholders. - Keep abreast of the latest developments in the fields of machine learning, Web3, and blockchain technologies to ensure our solutions remain innovative and competitive. Requirements: - Master's degree or higher in Computer Science, Data Science, Statistics, or a related field, or equivalent experience. - 5+ years of experience in machine learning, data science, or a related discipline, with a proven track record of successful project delivery. - Strong understanding of Web3 technologies, including Ethereum, smart contracts, and decentralized applications (dApps). - Familiarity with Rollups solutions (e.g., Optimistic Rollups, ZK-Rollups) and their integration in blockchain ecosystems. - Proficiency in Python, with experience using ML libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. - Solid understanding of a wide range of machine learning algorithms, statistical methods, and data preprocessing techniques. - Excellent problem-solving, analytical, and communication skills, with the ability to convey complex technical concepts to both technical and non-technical audiences. - Experience working with large datasets and distributed computing tools (e.g., Hadoop, Spark) is a plus.

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