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Experience working with machine learning frameworks (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) and distributed big-data tools (e.g. Spark) is a plus. 2+ years of professional experience as a MLOps Engineer, Data Engineer, or equivalent role, focusing on machine learning and/or ML infrastructure.
$110,000 - $142,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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As a Machine Learning Engineer, you'd be joining a talented and friendly team which loves to delight its customers with quality and robust code. Use off-the-shelf machine learning solution to provide simple initial solutions for fraud detection.
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Develop machine learning capabilities for image processing and data modeling. Proficiency in EDA, Modeling, and Machine Learning in R and/or Python. DISH Wireless seeks a skilled Data Scientist to join the Network Data and Analytics (ND&A) team within Network Development.
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As a Data Engineer/Data Scientist specializing in Azure, you will be responsible for designing, implementing, and maintaining data pipelines, analytics solutions, and machine learning models on the Azure cloud platform.
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You will work as part of a cross-functional agile team that includes data scientists, machine learning engineers, software engineers, designers, and product managers. 4+ years of hands-on experience in one of the following technical domains: machine learning, recommendation systems, pattern recognition, NLP, artificial intelligence, or a related technical field.
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Partner with diverse technical teams including software engineering, data engineering, machine learning, CRM developers, and data science to develop seamlessly integrated solutions spanning first and third party assets that collectively provide a cohesive end-user experience.
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Experience in Data Science and Machine learning, data mining and segmentation techniques. Experience with business intelligence tools, Enterprise Reporting and data visualization tools (PowerBI, Tableau, Qlik etc.
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SQL: 1+ Years (Preferred) Data Warehousing (Snowflake, Databricks, Redshift, BigQuery, Clickhouse, etc). Associate Cloud Data Engineer - Remote. Dive into a culture that values innovation, learning, and impactful work-all from the comfort of your home.
RemoteExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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The department houses a Bachelor’s degree in Geography with an optional GIS emphasis, a minor in GIS, and a certificate in GIS. We prefer candidates with expertise in remote sensing, field data collection, spatial data science, Earth data analytics, and/or machine learning.
$60,000 - $62,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure) Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark.
Full-timeExpandApply NowActive JobUpdated 28 days ago - UpvoteDownvoteShare Job
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Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.
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Thousands of enterprises including Cisco, DocuSign, Pacific Life, Slack, and TUI trust Matillion technology to load, transform, sync, and orchestrate their data for a wide range of use cases from insights and operational analytics, to data science, machine learning, and AI.
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Masters’ degree in data science, computational linguistics, data mining, machine learning, statistics, computer science, operations research, engineering, mathematics or related field required.
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Assist in Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. NLP, LLM, Gen AI Model Deployment: Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability.
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Experience in Machine, and Deep Learning frameworks, model validation and deployment tools, data pipeline technologies, and visualization and data storytelling tools (R, Tableau, Jupyter, etc.
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