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A deep technical background in applied data science, spanning some or all statistics, experimentation, machine learning, causal methods, optimization techniques, data engineering and architecture (applied to large data), and behavioral analytics.
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Involve in technical innovation through active research and applications of new theories, techniques, and technologies such as machine learning, deep learning /AI models (e.g., neural networks, convolutional neural networks, large language model) for complex clinical data analysis and prediction.
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Proficiency with common ML models such as Deep Learning, Logistic Regression, Decision Tree, Random Forest, XGBoost, FacebookProphet. Deploy sophisticated analytics programs, machine learning and statistical methods.
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Familiar with current and emerging techniques in analytics (machine learning, deep learning, AI) + Strong programming experience with R and/or Python for statistical modeling and other machine learning applications.
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Certification in machine learning and deep learning and/or predictive analytics. BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related fields and minimum 4 years related business experience in analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role OR advanced degree and 2 years directly related experience.
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Experience in mathematics (statistics, linear algebra, differential calculus); data visualization (Tableau, Power BI, Qlikview); programming (SQL, Python, R, Java); data analysis (feature engineering, data wrangling, EDA) and machine learning (classification, regression, reinforcement learning, deep learning, clustering, dimensionality reduction.
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Deep knowledge in machine learning, deep learning, and statistical modeling. Architect our machine learning platform at at internet scale. Lead your team to develop state-of-the-art (SOTA) Machine Learning models and features, applying rigorous offline and online testing methodology.
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Integrating innovative approaches in individual and team work products such as machine learning, artificial intelligence, data mining, predictive modeling, neural networks and simulation to mitigate price/value leakage across the pursuit and delivery phases of an engagement.
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The successful applicant will be responsible for developing a strong research program integrating data science approaches (advanced statistical techniques, machine learning, deep learning, AI or similar), data management approaches (curation and publication of reference data sets), latest sensor technology, and/ or advanced modeling techniques for applications in agricultural sciences.
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You will need both deep expertise in mixed-signal and analog design and breadth across other engineering disciplines, such as photonics and digital electronics, semiconductor device physics, thermal/packaging, and machine learning.
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Strong familiarity with topics of protein and macromolecular structures and interactions with other proteinsExperience with cloud environments such as AWSExperience in developing machine learning platforms using modern ML frameworks for deep learning (, tensorflow, keras, MXNet) & deploying in services such as Amazon Sagemaker.
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Subject-matter expertise in machine learning and deep learning recruitment & the ML industry. Provide full life cycle, high-touch recruiting support for our machine learning teams.
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Extensive exp in Computer Vision, Machine Learning, Deep Learning, or other relevant areas of Artificial Intelligence (e.g., as evidenced by industry experience, publication record.
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Keep up-to-date with emerging technologies and trends in data engineering, cloud computing, and machine learning, evaluating their potential impact on our systems and processes. This is a fantastic opportunity for a seasoned leader with deep technical expertise in data engineering and cloud architecture to leave a substantial mark in a swiftly progressing industry.
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Learn more about ADP at A little about ADP: We are a global leader in HR technology, offering the latest AI and machine learning-enhanced payroll, tax, HR, benefits, and much more. 10+ years relevant industry and functional experience in Database and Cloud-based technologies Experience in working with Machine learning and AI concepts related to RAG architecture, LLMSs, embedding and data insertion into a Vector data store.
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