Senior Data Scientist

Vaga não está no LinkedIn

🕒 Abril 24

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $58 - $93 / hora

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

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Foundation

SiteLinkedInTodas as Vagas

11 - 50 funcionários

₿ Cripto

🏪 Marketplace

🛍️ Comércio Eletrônico

💰 $200.000 Seed Round em 2021-02

Crypto • Marketplace • eCommerce

A Foundation é uma plataforma que facilita o comércio de tokens não fungíveis (NFTs), exibindo obras de arte digitais e ilustrações inspiradas em temas cósmicos e transformadores. Ela permite que artistas criem, vendam e exibam seus trabalhos em um mercado crescente, focando na interseção entre criatividade e tecnologia. A plataforma abraça a natureza evolutiva da arte em relação ao cenário digital, particularmente através da lente dos NFTs e da tecnologia blockchain.

Descrição

• Query, curate, and analyze large, complex healthcare datasets • Generate insights that improve cancer care delivery • Apply statistical modeling, machine learning, clinical NLP, and large language model-enabled information extraction • Identify patterns in longitudinal data • Transform clinical notes into structured, research- and operationally useful variables • Build predictive models • Deliver actionable solutions for clinical, research, and decision-support workflows • Collaborate with administrative leaders, clinicians and IT specialists • Design and implement pilots for validation and optimization of models in real time • Produce technical documentation, visualizations and presentations • Lead projects with multiple work streams or complex tasks • Project management for complex tasks • Complete individual or collaborative projects independently • Provide key subject matter expertise and leadership in advancing the use of AI technologies in precision medicine and clinical decision support • Provide mentorship and guidance to more junior staff • Performs other related duties as assigned or requested

🎯 Requisitos

• PhD degree in computer science, engineering, statistics, mathematics, physics, or fields related to data science with 0+ years of experience as a data scientist, Master’s degree with 3+ years of experience; or Bachelor’s degree with 5+ years of experience • Familiarity with a health care environment and EHR data • Familiarity with genomics and medical imaging data • Time series analysis • Natural Language Processing (NLP), including clinical NLP and large language model applications for unstructured clinical data. • Cloud services platforms like Amazon AWS and Microsoft Azure • Awareness of the most recent trends and developments in the Data Science / Machine Learning fields • Data analytics expert with measurable track record within industry or academic environment, developing and successfully implementing statistical and machine learning models for data mining, classification, prediction and clustering • Experience with relational databases and SQL queries. • Must be knowledgeable in at least one scientific computing language such as Python (e.g. pandas, scikit-learn, genism, seaborn, tensorflow), R (e.g. caret, dplyr, ggplot2), and Matlab • Solid experience in Machine learning (RandomForest, XGBoost/ LightGBM, etc.) and deep learning (CNN, RNN, LSTM, etc.) techniques • Proficiency in at least one programming language (e.g. Python, Java, C/C++) • Ability to work independently and use creative approaches to problem- solving • Capable of turning questions into testable hypotheses, extracting data from complex databases, creating and evaluating statistical models • Experience in data visualization and ability to communicate results to a non-technical audience • Experience in completing end to end projects with minimal to no supervision • Experience in being a part of big projects with many internal and external teams involved • Experience managing collaborative data science projects • Experience mentoring or leading teams of data scientists • Strong track record of data science publications, or extensive experience in developing production grade models and managing them in production • Information extraction from clinical notes • Longitudinal EHR/claims data • Evaluation of production-grade clinical AI systems