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Experience working with cloud or on-prem Big Data/MPP analytics platforms (i.e. Clickhouse, Spark, Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar.
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Solid understanding of machine learning, deep learning frameworks, neural network architectures, and the principle of neural network engines. The individual will be responsible for delivering optimized Machine Learning model development and related product implementation supporting different lines of business.
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Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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Apply various Machine Learning technologies (Deep Learning - Natural Language Processing, Autoencoder; Traditional Machine Learning - Isolation Forest, Decision Tree, Random Forest, XGBoost, & LightGBM, advanced analytics (Python, SQL, and AWS) and visualization techniques to extract and analyze various datasets across the company.
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Manage services from Public Cloud Hyperscalers like Microsoft Azure, Amazon AWS, Oracle OCI, Google GCP, and Alibaba Cloud on services like Cloud Compute, Storage Services, Data Services, DevOps, CI/CD, MicroServices, Service Mesh, Containerization, Artificial Intelligence, Machine Learning platforms and End-to-End Observability.
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As a new company with minimal tech debt and big ambitions, there will be many opportunities to hone your existing skills as well as explore new areas of technical and non-technical growth (full stack and backend development, product, data engineering and machine learning, business operations, management, etc.
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Information Technology, Consulting, Artificial Intelligence, Software Development, Data Science, Machine Learning, Data Analytics, Cybersecurity, Computer Software, Information Technology and Services.
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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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4+ years of related work experience in the field of Data Science & Machine learning. You will be pivotal to the growth of our data science team and instrumental as we continue to build a team of data scientists and machine learning engineers that can increase customer engagement and stickiness on our sites while improving the quality of the leads to our partners.
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As an ML Ops and Data Engineer at our Machina Labs, you will play a pivotal role in the integration of machine learning models, data pipelines, and operational processes to optimize the performance and functionality of our robotic systems.
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Create data processing pipelines and software to support critical control, data collection, and machine learning systems. Familiarity with data acquisition systems, sensor data integration, and processing.
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Stay ahead of emerging technologies and methodologies in data engineering and machine learning. Metropolis is seeking a Senior Machine Learning Data Engineer to play a crucial role in architecting, implementing, and managing our ML data ecosystem to support advanced machine learning initiatives.
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We are industry leaders in embedding technology, leveraging data analysis, machine learning, and artificial intelligence for a broad range of Deal-focused solutions. Certifications within predictive modeling and/or machine learning platforms such as Python, SAS, etc.
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TEAM: Machine learning and data science is the core part of the company. Work with data scientists to build end-to-end machine learning models to model customer behavior in the credit space.
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Create and support AWS based data platforms that leverage diverse data sources across Amazon, that feed input to and serve output from machine learning / econometric models.
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data machine learning aws jobs in Torrance, CA
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