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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Conduct research on cutting edge technologies in AI/BI/ML/NLP, alternative data, FinTech, high performance computing (e.g. GPU, quantum computing) to discover the potential opportunities to the business applications.
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ML Ops: Design and Build customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domainsTechnical Expertise: Serve as the subject matter expert on AI technologies, including machine learning, natural language processing, computer vision, and other relevant domains.
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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 1 month ago - UpvoteDownvoteShare Job
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The ideal candidate will have a strong background in SQL Server development, hands-on experience with Azure Pipeline, and proficiency in working with Databricks for data processing and analytics.
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Our Engineering team is seeking engineers with strong skills and hands-on experience in designing, constructing, and optimizing large-scale distributed systems, with a particular emphasis on machine learning infrastructure.
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You should possess strong technical skills in SQL, Python, Spark, and PySpark and have hands-on experience with AWS and Databricks platforms. You will be responsible for implementing and maintaining data solutions on AWS and Databricks platforms.
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High systems aptitude and comfort with learning new technologies; experience in Google Suite and strong Excel skills required; SQL, BigQuery, and/or Tableau experience preferred. We do not discriminate on the basis of race, color, creed, religion, gender (including gender identity or expression), pregnancy, childbirth or related medical conditions, sexual orientation, marital status, domestic violence, sexual violence or stalking victim status, ancestry, national origin, alienage or citizenship, age, disability, military or veteran status, genetic information or predisposing genetic characteristic, or other protected status.
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Keep on top of Duck Creek Technology Product Roadmap and the industry trends including Digital Transformation, InsureTech, AI/Machine Learning etc. Hands on knowledge of Duck Creek Policy , Duck Creek Author, SQL Server etc.
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Advanced degree preferred, with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
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Understanding of strengths and weaknesses in application of Machine Learning and Artificial intelligence to applications in Transaction monitoring and Sanctions screening. Hands on programming skills required in common programming languages and packages like R, Python, C.
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Your office will be located in this brand-new 80,000 square-foot ambulatory facility complete with MA’s, RN’s, PA’s, urodynamics, EPIC EMR, full-service on-site imaging center with brand new Siemens MRI and PET CT, ultrasound, and on-site lab.
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That restorative justice, inquiry-based hands on learning, and authentic learning experiences provide the most effective environments for growth, success, and joy. Providing regular one-on-one counseling and/or group counseling to students and families.
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Minimum THREE (3) years of hands-on experience implementing Collibra data catalog, data governance, data lineage, data privacy, and data quality capabilities.
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Hands on experience in dealing with structured and unstructured data from multiple sources and applying machine learning techniques and algorithms to discover patterns, intents and build knowledge repositories and graphs to solve enterprise problems.
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