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Experience leveraging complex data to drive business decisions, hands-on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Python, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
Full-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Requirements: Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics or a related field and ten (10) years of progressive, post-baccalaureate experience as a Director – Principal Engineer or related occupation in data engineering and big data applications.
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Experience in software engineering, including hands-on expertise in ETL/Data pipeline and data lake platforms like Databricks, Spark/Hadoop, and Snowflake. As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Technology Engineering and Architecture team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way.
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You are very skilled at using one or more BI tools (e.g. Tableau, Sigma, Looker), cloud data warehouses (e.g. Snowflake, Redshift, Big Query), data transformation frameworks (e.g. dbt), and data science tools (e.g. Python/Jupyter, Julia, R.
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Bachelor’s degree or above in quantitative or engineering fields (Statistics, Economics, Mathematics, Health/Medical Informatics, Computer Science, or similar) The primary objective of the Data Organization is to harness healthcare data to support and promote value-based care contracts between health systems, providers, health plans, and other third-party risk bearing entities; incentivize quality, utilization, and experience outcomes; and enhance payment operations with both services and product development.
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Primary responsibilities for Assistant Professor will include teaching a range of computer science courses like programming, web development, software engineering, artificial intelligence/machine learning, cloud computing, cybersecurity, data analytics/data science, blockchain.
$75,465 a yearFull-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
$172,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Hands-on experience and specialization in various data and analytics disciplines including some of the following (data engineering, ETL/ELT, ML/AI, streaming, API integration and development, data/dev ops, data science, data virtualization.
Full-timeExpandApply NowActive JobUpdated 16 days ago - UpvoteDownvoteShare Job
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You will be able to demonstrate knowledge and expertise in data engineering best practices and concepts using Databricks. Predictive, Prescription, and Descriptive Analytics using Data Science tools and technologies.
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You will provide a range of qualitative and quantitative consulting services in the areas of data science, AI, model development, model validation, model risk management, modeling technology, model governance / controls / documentation, and financial instrument valuation.
$207,763 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Software Engineering/Data Engineering: data ingestion, streaming technologies - such as Spark Streaming and Kafka, performance tuning, troubleshooting, and debugging Spark or other big data solutions.
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Bachelor's degree in Computer Science, Data Engineering, Machine Learning, or a related field is required. Manage and build high-performance Data Engineering and Machine Learning Engineering teams, fostering a culture of innovation and excellence in a remote-first environment.
$230,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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You have the ability to describe your ideal analytics schema to data engineering team members and work with them to improve a data warehouse. You will collaborate with engineering teams, data scientists, product managers and client success managers to help develop business logic and detailed system requirements and to help identify and answer research questions of interest to the company and our clients.
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As a Marketing Data Science Intern, you will collaborate with experienced data scientists and marketing professionals to support data-driven strategies for optimizing marketing effectiveness.
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data science big engineering jobs Title: machine learning engineer in New York
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