Arity · 2 days ago

Machine Learning Scientist

Illinois, United States

Full-time

Remote

Senior Level

$122K/yr - $207K/yr

7+ years exp

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Information ServicesInformation Technology

Work & Life Balance

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Responsibilities

Working with large geospatial data sets using distributed computing frameworks

Building spatial and machine learning models using a variety of libraries/tools and cutting-edge techniques

Identifying opportunities for new machine learning solutions, exploring new data sources for enrichment, collecting appropriate labels for learning, establishing actionable metrics, and creating reusable model validations and risk mitigation

Communicating results to key stakeholders in a clear and compelling manner

Applying appropriate methodologies for the problem and validating the solution with the appropriate metrics

Establishing and following data science best practices including peer review, code review, documentation, coding standards, and ensuring reproducibility and compliance

Expanding machine learning skillset through development opportunities and researching innovative tools and techniques to level up capabilities

Qualification

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Machine LearningModel DevelopmentModel DeploymentModel MonitoringModel Life-Cycle ManagementPredictive ModelsEnsemble AlgorithmsDeep Neural NetworkGraph Neural NetworksConvolutional NetworksTransformer ArchitecturesScientific ComputingScikit-learnTensorFlowPyTorchSpark ML-libAI PlatformsVertex AISagemakerGeospatial DataUS Census DataWeather DataParcel DataPOIProduct Requirement TranslationAnalytical Problem DefinitionData InterpretationProblem-SolvingCommunicationSpark/SQL

Required

Master’s or PhD degree in a machine learning/AI related field such as engineering, statistics, computer science, physics, or related discipline

Over 7 years' experience with developing end-to-end machine learning solutions/algorithms including model development, model deployment, model monitoring, and model life-cycle management

Demonstrated advanced knowledge in predictive models such as parameterized methods, ensemble algorithms, deep neural network, large language models, graph neural networks (GNNs), convolutional networks, transformer architectures

Experience with scientific computing libraries Scikit-learn, TensorFlow, PyTorch, Spark ML-lib

Experience with deploying ML models using AI platforms such as Vertex AI and Sagemaker

Experience with geospatial data is highly preferred, such as US census data, weather data, parcel data, POI, etc

Ability to translate product requirement into well-defined analytical problems

Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise