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You are passionate about learning and applying new techniques within data science that leads to innovations. ADP is looking for the next generation of Data Scientists to join our: Data Scientist/Machine Learning Development Program (Full-time.
$48,400 - $129,780 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Fama is seeking a Junior Machine Learning Engineer to join our Data Science and Analytics team to advance the next generation of our AI/ML infrastructure. Strong bonus experience: 1 - 2 years of deep learning/computer vision/natural language processing/machine learning/computer science with equivalent industry experience (or, in exceptional cases, BS with a proven track record of relevant industry or transferrable experiences.
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Promote knowledge sharing and learning within the data science team and across the organization. Utilizing deep learning tools such as TensorFlow, Keras, or PyTorch to train diverse neural network architectures.
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We are seeking a highly skilled and experienced Sr. Machine Learning Engineer / Data Scientist to join our dynamic Data Science and AI team. Proficiency in cloud platforms such as Azure Synapse Analytics, Azure Machine Learning, AWS, and Google Cloud Platform for deploying big data and ML solutions.
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Looking for experience with the following: DevOps, CI/CD, Docker, Kubernetes, AWS Sagemaker, GenerativeAI (GenAI - ChatGPT), Large Language Models (LLM), Natural Language Processing (NLP), Neural Network (NN, CNN), Deep Learning.
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Demonstrated experience with implementing data science workflows in cloud-based platforms (e.g., AWS, Azure, etc. Demonstrated experience using CUDA and NVIDIA GPU accelerated libraries for AI, machinelearning, and deep learning.
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Real world experience as an ML engineer or data scientist role building and deploying ML models or developing deep learning models, with experience in at least 3 of the 5 key machine learning algorithms: Ridge Regression and Lasso, random forests, linear optimization models, sensitivity analysis, and boosting model.
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Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
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You will work on a wide range of initiatives, whether that’s building ETL pipeline, or training a retrieval re-ranker, or working with the DevSecOps team to build the CICD pipeline, or designing a Generative AI Infrastructure that conforms to our strict security standards/guardrails, or working with the data science team in their pursuit of improving the accuracy of the LLM models.
Full-timeRemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Machine Learning (e.g., regression, classification, deep learning, unsupervised learning) and/or Machine Learning Model Development. Data Analysis, Data Engineering, Data Science.
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11 West 19th Street (22008), United States of America, New York, New YorkManager, Data Science - Fraud, Deep LearningManager, Data Scientist, Fraud. The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters.
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Works with executive leadership to identify data science project opportunities and assists in planning activities including budget and scope determination. As a Machine Learning (ML) Engineering Manager Sr you will lead a team of ML Engineer and Software Developer's to deploy machine learning models in production environments at scale.
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Experience with big data technologies (e.g., Hadoop, Spark, Databricks, Snowflake) and cloud platforms (e.g., AWS, Azure). Strong proficiency in statistical analysis and modeling techniques, such as linear regression, logistic regression, decision trees, random forests, clustering, deep learning algorithms, boosting, text mining and NLP.
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As part of the AWS Analytics science team you will have the opportunity to apply your machine learning skills to impact some of the largest analytics services in the industry and their customers.
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Five (5) years of experience with machine learning algorithms and tools, artificial intelligence, deep learning, and Cloud infrastructure preferably AWS. Advanced/post-graduate degree in computer science, Data Science, Statistics, or a related technical field.
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