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TensorFlow, PyTorch, Keras (for deep learning and complex machine learning, including neural networks and advanced AI) AWS SageMaker (for end-to-end machine learning development, training and scalable machine learning in a managed cloud enviornment.
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Data Science & Machine Learning Frameworks. CI/CD Pipelines (for automating deployment and monitoring of machine learning models) Python (for preprocessing, data analysis, machine learning, scripting.
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Experience with machine learning and statistical analyses are needed. Scikit-Learn (for classical machine learning) Develop and implement algorithms on existing data warehouse records and identify new external data sources to be ingested to the data warehouse to strengthen analyses.
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Comprehensive understanding of machine learning and NLP algorithms, with hands-on experience in frameworks like Scikit-Learn, TensorFlow, and PyTorch. Hands-on experience with LLM application frameworks, such as Langchain.
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Use machine learning, deep learning, and reinforcement learning techniques to develop robust solutions for account takeover detection, payment fraud detection, fake account signup solutions, and identity risk assessment.
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Under this program, we will make you stand out from the rest of the jobseekers by offering Skill enhancement training on the technologies in-demand including time management skills, study skills, test-taking skills, and learning strategies after which we can assist candidates in getting jobs as software programmers / Java Programmers / Data scientists / Machine learning engineers / Data analysts.
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Production-level experience with core quantitative analysis techniques (e.g., predictive modeling, machine learning, artificial intelligence, or natural language processing) in a consulting environment.
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Clinical Terminologies (e.g., SNOMED, LOINC) Data Warehousing (e.g., AWS Redshift, Google BigQuery) Natural Language Processing (NLP) (for analyzing clinical notes or electronic health records) Apache Hadoop or Apache Spark (for big data processing.
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Experience in developing machine learning solutions for problems. Develop novel deep learning techniques to achieve state-of-the-art accuracy within the constraints of on-device and real-time execution on CNN, LLM and multimodal models.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data) Docker, Kubernetes, ECS, EKS or AWS Fargate (for containerization and orchestration of data applications and reproducibility.
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Data Visualization Tools (e.g., Tableau, Power BI, Plotly) ETL Tools (e.g., Informatica, Talend, AWS Glue) Bachelors Degree computer science, artificial intelligence, informatics or closely related field.
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AWS Bedrock (for accessing pre-trained LLMs and foundation models without managing infrastructure) Experience with Epic or Cerner (popular EHR systems in healthcare) AWS, Google Cloud, or Azure (cloud platforms for scalable computing.
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SQL-based Databases (e.g., PostgreSQL, MySQL, Microsoft SQL Server) The Data Scientist will be responsible for driving insights from the vast amounts of patient and environmental data available within our data warehouse.
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ICD-10 Coding (for medical diagnosis and procedure classification) HL7 (Health Level Seven International standards for electronic health information exchange) Electronic Health Records (EHR) Systems.
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hands on machine learning jobs Title: solutions architect Company: Databricks Inc in Laramie, Wyoming
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