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In addition, the group extracts relationships insights by applying - distributed - graph, machine learning, and natural language processing algorithms on this Knowledge Graph, as well as on other text document collections, and feeds these insights, via means of reliable and scalable APIs, UI applications, and mobile applications, to several other firm products and employees across multiple divisions: Compliance, Investment Banking, Global Markets, Asset Management, to name a few.
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We employ scalable cutting-edge machine learning (Client), deep learning (DL), and Natural Language Processing (NLP) knowledge to better target customers and prospects, understand and personalize the content, and context needed to optimize their book-listening experience.
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And big data pipelines and databasesExperience in AI applied research, preferably in Natural Language Processing (NLP) and industrial recommender systemsExperience as the tech lead for an engineering or research teamA high bar for engineering excellence in terms of practices and processesBenefits are an essential part of your total compensation for the work you do every day.
$149,200 - $234,850Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.
$195,800 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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The candidate should have expertise in data modeling, SQL, Python, R, data warehousing, big data technologies, data pipeline construction, data quality, cleansing, version control, cloud services, machine learning, feature engineering, deep learning, and natural language processing.
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Experience in Natural Language Processing (NLP) Experience in Big Data environment specifically PySpark and/or Databricks. Demonstrated experience in working with assignments that involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors with Python, R, SAS, SQL, MATLAB, DataRobot or similar statistical and scripting tools.
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We are looking for a Senior Data Scientist who will design studies and utilize cutting-edge predictive modeling techniques, test rigorous hypotheses, and turn data and insights into actionable plans.
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Being part of a talented team of Data Scientists with broad skills and applications, the Senior Data Scientist will work cross-functionally and collaboratively with teams across the enterprise through innovative machine learning, R&D, and cutting-edge platforms.
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We seek a talented and dedicated software engineer to support Machine Learning/Natural Language Processing (ML/NLP). Experience with big data and cloud computing environments, Azure and Snowflake preferred.
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Several faculty members in the EECS department are NSF-funded and publish in top research venues, with concentrations in big data, computer networks, natural language processing, machine learning, and artificial intelligence.
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Reporting to the Sr. Director, Data Management, the Director, Data Management is responsible for the oversite of Data Management vendors to ensure timelines and deliverables are met and is accountable for all aspects of the clinical trial data management process from study start up through database lock, including escalations of issues when necessary.
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As needed, collaborate with internal and external stakeholders to identify object detection, optical character recognition, automation, predictive modeling, pattern analysis, natural language processing, fraud detection, and other business cases for using ML.
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Experience working with big data distributed programming languages and ecosystems such as Hadoop, MapReduce, Pig, or KafkaExperience with designing and building cloud-based databases, data lakes, and data warehouses.
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Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB. Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc.
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