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SpotHero is seeking a Senior Machine Learning Engineer to join the Data Science squad. Bachelor’s degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field with 6+ years of professional experience in data science/machine learning.
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Cloud Computing – Use the full range of Microsoft Azure Services with exposure to machine learning. We are working on challenging projects, migrating ETL jobs from Talend to DataBricks, building workflow automation solutions using Microsoft Power Platform, data flows with Azure data lake storage and DevOps environment set up.
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Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
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Design, develop and monitor large scale data pipelines empowering executive dashboards, operational reporting, and machine learning algorithms. The Data Engineer is a key member of WellNow’s Data Operations team.
$110,000 a yearFull-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Focus on the development and application of new methodologies, technologies, and techniques to gather data and insights including machine learning AI, mobile optimization, gamification, behavioral economics, and virtual/augmented reality.
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Using tools such as SQL, DataBricks, Talend, Python, Microsoft Power Platform and Azure Data Factory. Continuous Learning – stay up-to-date with emerging technologies, changes in the banking industry, and regulatory developments.
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The LCRR Regional Lead will work closely with the Specialized Solutions group to apply dashboarding capabilities, advanced data analytics, and machine learning for predictive modeling of SL material identification but will not be responsible for development of these tools.
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Interpreting and delivering impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps. Advanced proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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Innovation: Focus on the development and application of new methodologies, technologies, and techniques to gather data and insights including Machine learning AI, Mobile Optimized Surveys, Gamification, Behavioral economics, real-time feedback, Multimodal surveys, Blockchain technology, Virtual and Augmented reality.
$160,000 - $284,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Develop and implement data ingestion, transformation, and validation processes to ensure data quality, consistency, and reliability across various healthcare datasets. Mentor and guide junior data engineers, fostering a culture of collaboration, learning, and growth within the team.
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CI/CD Implementation : Utilize CI/CD tools to automate the deployment of data pipelines and infrastructure changes, ensuring high-quality data processing with minimal manual intervention.
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You Have: 3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. Experience working in vector databases like Milvus, Pinecone, or Weaviate Experience using machine learning in data pipelines to discover, classify, and clean data.
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You Have: 8+ years of experience in batch and streaming ETL using Spark, Python, Java, Snowflake or Databricks for Data Engineering or Machine Learning workloads. #StartWithTheCustomer You will be focused on managing a team who are building and operating data pipelines that power analytics and modern machine learning models.
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Machine Learning, AI & GenAI: Proficiency with deep learning frameworks such as TensorFlow. PhD or Master's degree desired, preferably in Computer Science, Engineering, Machine Learning, Statistics, Economics, Physics, or a similar field with quantitative coursework, or equivalent work experience.
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Basic knowledge of digital manufacturing technologies such as digital twin, artificial intelligence, and machine learning, as well as cybersecurity guidelines and frameworks, including NIST and CIS.
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machine learning data quality jobs Title: data engineer staff in Chicago, IL
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