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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
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Familiarity with cloud-based data storage and processing technologies for handling large datasets efficiently. Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow.
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Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Bachelor’s Degree in related field (e.g. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT.
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Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB. Fuse's innovation culture and modern product development teams power the evolution of our commercial products and spark the creation of new businesses and products.
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The Opportunity 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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Experience in the Design and implementation of AI/ML models and solutions using Google Cloud Platform technologies, including but not limited to Vertex AI , BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine.
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Experience with Natural Language Processing (NLP), computational linguistics, Entity extraction, named entity recognition (NER), name matching, disambiguation, Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA.
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Experience with machine learning related open source libraries including, but not limited to: Hadoop, Spark, SciKit-Learn, TensorFlow, etc. Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Our work spans many disciplines, such as information retrieval, natural language processing, and machine learning. Experience with a variety of High-Performance computational frameworks (Spark, Hadoop, Elasticsearch, Kafka, AirFlow, etc.
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Experienced with traditional as well as modern machine learning/statistical techniques, including A/B testing, Causal Inference, Regression, Classification, Ensemble Methods, Deep Learning, Natural Language Processing, and Reinforcement Learning.
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Experience working with Python, R, Natural Language Processing (NLP), AI/ML Ops. Additional preferred qualifications include working with unstructured text and natural language processing.
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Knowledge applying advanced statistics to complex business problems required (e.g. modeling, AI, ML, Deep Learning [DL], and/or Natural Language Processing [NLP]). Experience working with a variety of statistical languages/packages, e.g., SAS, R, Python, Spark, and/or SPSS required.
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