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Fluency in the languages of data manipulation (e.g., SQL) and statistical analysis (e.g., R or Python/NumPy), with ability to code (e.g., PHP) a plus, Java, Ruby, Clojure, Matlab, Pig or SQL. Background in Artificial Intelligence (AI), Machine Learning (ML) Natural Language Processing (NLP.
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This is an opportunity to lead the Enterprise Tech Data Management and Privacy while heavily influencing the Enterprise Machine Learning Platform and Enterprise Real-Time Event Processing & Analytics Platform to support the end-to-end development and execution of Amex's data management initiative.
$110,000 - $190,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with machine learning technology, such as: big data stack, Java, Python, R, Scala and visualization techniques, including Dash, Tableau and Angular. Expertise in machine learning technology, such as: big data stack, Java, Python, R, Scala and visualization techniques, including Dash, Tableau and Angular.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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The candidate will be working with the following state of art technologies; Solr, Lucene, Natural Language Processing, Machine Learning, Linux, Groovy, Python, Splunk, Prometheus, Grafana, DevSecOps, Jenkins, Maven, Gitlab, Nexus, Ansible, TDD, BDD, JMeter, Selenium, and other open source frameworks.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Use programming languages including but not limited to Python, R, SQL, Java or Scala, SQL. Programming Languages: Python, R, SQL, Java or Scala, SQL. As a Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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You have/had hands-on experience with Python, Java or Scala and the ability to write reusable and efficient code to automate machine learning pipeline and data processes. Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$132,000 - $264,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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As a Director, Data Scientist on/in the US Businesses Long Term Care Data Science Team you will partner with Machine Learning Engineers, Data Engineers, Data Analysts and other professionals to build models to determine Long Term Care Estimates.
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As a Vice President, Data Science Lead for Finance and Actuarial, you will partner with Machine Learning Engineers, Data Engineers, Data Analysts and other specialists to transform financial and actuarial processes by building state-of-the-art actuarial, financial, and behavioral models.
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We are looking for an engineer with prior advertising/sales/marketing software experience (Hubspot/Salesforce) to help integrate those tools with our core applications (Java/Python) and datastores (Snowflake/MongoDb.
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Strong understanding of machine learning principles, especially in the context of LLMs. 5+ years of proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch Skills in Java/scala (preferred) Experience building scalable deep learning systems.
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