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Master’s Degree or Ph. D. in Data Science, Operations Research, Psychometrics, Marketing Science, Finance, (Bio)Statistics, Econometrics, Computer Science, Applied Mathematics, or another quantitative field.
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Azure Data Engineering or Databricks Certification, and expertise with other cloud data platforms (AWS, Snowflake) preferred. - Lead the design and implementation of complex cloud solutions using Microsoft Azure, focusing on integration with Databricks and Azure Data Factory.
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KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.
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Familiarity with BMIDE (Business Modeler Integrated Development Environment) and its utilization for configuring and customizing Teamcenter data models, data types, and data structures.
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As a Senior Data Engineer on the MMA National IT Data and Analytics Team, we will count on you to develop and maintain scalable data pipelines, enhance data models, and provide subject matter expertise in data acquisition and consumption pipelines on Azure, Databricks and Confluent.
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This is an excellent opportunity for a talented Azure Data Engineer who is looking to advance their skills and work with cutting-edge technologies in the Information Technology and Finance industry.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
$195,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are seeking a skilled Data Science Engineer who will be responsible for overseeing the maintenance and improvement of current machine learning implementations within our Revenue Cycle line of business.
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Data Management and Integrity: Maintain data accuracy in the Workday Adaptive Planning tool by managing non-labor access and ensuring data integrity across all financial processes.
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Assist the team that will document, maintain, and tune AML transaction monitoring rules, sanctions screening systems, and risk scoring models as well as detailing data lineage and model/rule assumptions and parameters for all models.
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Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, Google Cloud Platform, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
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Provides complete and consistent documentation of data warehouse content in the Caboodle Console to ensure that users can determine what data is available in the warehouse, how this data is defined, and lineage to Epic Clarity.
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Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools. We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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These research systems handle high data rate digital signal processing and beamforming, interfacing with accessory devices, memory, and networks using bare-metal and real-time processing. Sonar, Acoustics, Medical Ultrasound, Radar, Maritime Research, Signal Processing Algorithms and Techniques.
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Strong understanding in the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Ray, LangChain, Data lake house (Databricks), Snowflake, SageMaker, Scikit-learn, etc.
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data job Title: finance director in Austin, TX
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