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State Street’s Bionics team has the mission to explore, enable and exploit artificial intelligence, machine learning, natural language processing, computer vision and cognitive computing at scale for multiple use cases across Global Delivery, Global Advisors, Global Markets, and Global Exchange business lines.
$100,000 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Leverage AI and machine learning technologies, such as TensorFlow, Vertex AI, and AutoML, to enhance data insights and drive business value. Knowledge of AI and machine learning technologies, such as TensorFlow, Vertex AI, and AutoML.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. Difference between Machine learning, Artificial Intelligence and Deep learning.
$75,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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1+ years of hands-on experience in one of the following technical domains: machine learning, recommendation systems, pattern recognition, NLP, artificial intelligence, or a related technical field.
$122,000 - $153,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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We're seeking a Business Intelligence Lead with a strong background in healthcare data operations and a passion for data quality and process improvement. As a Business Intelligence Engineer for CenterWell Primary Care, you can directly impact patient care and outcomes through your work.
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Integrating innovative approaches to 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.
$113,200 - $205,500 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Join us as a Senior Machine Learning Engineer specializing in Natural Language Processing (NLP), where you will tackle some of the most exciting challenges in the field today. This role involves working with state-of-the-art machine learning and deep learning algorithms, focusing on next-generation AI technologies such as large language models, generative AI, retrieval-augmented generation, LLM agents, and fine-tuning techniques.
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Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc.
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Databricks Certifications (ie: Data Engineer Associate; Data Engineer Professional, Machine Learning Associate, Machine Learning Professional) 2+ years experience implementing data solutions on the Databricks Data Intelligence platform, to include Delta Lakes.
$119,025 - $198,375 a yearFull-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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When not working on machine learning models, Identify data; define metrics and analyze needs for business partners; Initiate, develop and maintain data pipelines and data models that powers dashboards and data products with outstanding craftsmanship.
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As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Explore and identify Spice modeling components for efficiency and quality improvement with Artificial Intelligence (AI) and Machine Learning (ML). Requires three (3) years of experience in: (1) data analysis with Python and Python machine learning packages; (2) creating analytics tools to visualize KPIs in relation to equipment and process engineering; (3) MS Excel Macros and Pivot tables; (4) SQL, Tableau, and Spotfire; (5) knowledge of semiconductor process.
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The primary mission of the team continuously ships pragmatic solutions utilizing applied Artificial Intelligence and Machine Learning that deliver value for our Medical Professionals users.
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As a Business Intelligence Manager, you will own the delivery of actionable insights to inform data-driven decisions on sales & marketing strategy, and increase efficiency of our go-to-market operations.
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Bachelor’s in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Partner with Product and Data Solutions teams to design, build, and deliver machine learning models and components to address business challenges.
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business intelligence machine learning jobs Company: Dice in Austin, Norwood, Massachusetts
FEATURED BLOG POSTS
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The summer had economists from around the globe embroiled in a debate about a possible recession coming in the next few years (or months). As of October 2022, the U.S. Labor Department data put the current inflation rate at 7.7%. The recent layoffs in the tech industry are just the first of what is soon to be a string of cutbacks by companies looking to save costs. For recruiters, this means freezes in hiring and fewer openings. It will also include the uphill task of finding the best candidates for them from the coming influx of recently laid-off job seekers. Now is probably a good time to brace for tough times in the next few years in the talent acquisition industry. To survive and thrive recruiting in a recession, here are some hard truths you will need to accept.
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Email Etiquette Principles - Why is it Important
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"Nothing we do is more important than hiring and developing people."
Collaborative Recruiting: The Key to a Better Talent Acquisition Strategy
Talent acquisition is a multi-stage process where candidates undergo various application steps before getting hired. The unfortunate reality is that it is a labor-intense system, with the hiring manager and recruiter often handling all of the work on their own. Ask any one of them, and you will hear about the overabundance of applications and the demanding task of filtering through them to find the best candidates. The quality of talent suffers under the weight of all that work on one person's hands. It's not easy, but as many companies are starting to realize, there is a better way. The future of talent acquisition lies in collaborative recruiting!