Data Scientist

Job not on LinkedIn

🕒 April 9

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Foundation

11 - 50 employees

₿ Crypto

🏪 Marketplace

🛍️ eCommerce

💰 $200k Seed Round on 2021-02

Crypto • Marketplace • eCommerce

Foundation is a platform that facilitates the buying and selling of NFTs (Non-Fungible Tokens). It provides a marketplace where artists and collectors can connect and trade digital artworks and collectibles, often expressed in Ethereum cryptocurrency. The platform features various trending and featured works, including exhibitions and galleries presented by different artists or collectives. Foundation Labs operates with a focus on the digital art community, providing a space for creators to showcase their work to a global audience.

📋 Description

• Query and analyze large complex datasets to discover insights to apply to an evolving cancer care delivery environment • Use data mining, statistics and machine learning to understand relationships and patterns in data • Build predictive models and propose actionable solutions • Support drug discovery and biotherapeutics efforts by applying advanced molecular simulation and modeling techniques • Perform quantitative modeling of complex chemical and biological systems • Translate scientific data into reliable predictive models • Build machine-learning pipelines that can be validated and adapted as project priorities evolve • Collaborate with administrative leaders, clinicians and IT specialists • Query large datasets from multiple systems • Build machine learning models • Design and implementation of pilots for validation and optimization of models in real time • Produce technical documentation, visualizations and presentations • Project management for complex tasks • Completes own work independently • Performs other related duties as assigned or requested.

🎯 Requirements

• Master’s degree in a quantitative biology or chemistry field with 0+ years of experience; or Bachelor’s degree with 3+ years of experience with knowledge in mathematical and computational modeling of molecules, analysis of technical datasets, model validation, machine-learning in life-science discovery workflows, and biochemical modeling and screening or optimization.

🏖️ Benefits

• Comprehensive Benefits

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