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Performance Tuning of Big data Hadoop Platforms ( Cloudera , Horton work ). Performance tuning of Cloudera/Horton work big data platforms. Strong experience in Cloudera/Horton work Big data platforms.
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Working knowledge of UiPath Cloud’s ecosystem of tools, including Orchestrator, Studio, Document Understanding, AI Center, Connectors, RE Framework, Integration Services, Data Service, Insights, Process Mining, Task Mining, Test Automation, etc.
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Incumbent should have an understanding of various database environments (IBM DB2, Oracle), technical programming skills (SAS, SQL, Toad), exposure to applied data science tools (R, Python, SAS E-Miner), familiarity with data visualization and BI tools (Tableau, MicroStrategy), and demonstrated proficiency in Microsoft Office Suite (Excel, PowerPoint, Word.
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Certified Analytics Professional (CAP), Data Science Council of America (DASCA), Principal Data Scientist (PDS), SAS Big Data Professional, Microsoft Certified Azure Data Scientist Associate, or equivalents.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. For data Science/Machine learning Positions. Preferred skills: NLP, Text mining, Tableau, PowerBI, Databricks, Tensorflow.
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Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning.
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The People Analytics team is globally respected as a leader in its field and is dedicated to staying on the cutting edge of business intelligence and data science methodology and technology.
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Bachelor’s or Graduate degree, Field of Studies required: In a quantitative field or commesurat experience such at Statistics, Business Analytics, Data Science, Applied Math, Econometrics or Operations Research.
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Perform sophisticated card fraud analyses and strategy support using advanced analytics & data science tools to provide actionable insights and real-time changes to card fraud detection tools that improve business outcomes and minimize fraud risk.
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You will have indepth knowledge and experience in; cloud data lake house; Databricks (preferred) or Snowflake; cloud-native solutions knowledge; SQL or Python; modern DevOps approach; have written data code AND also the CI/CD pipelines.
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Required Minimum QualificationsIntern Pursuing a Bachelor’s, Master's, or Doctoral degree in Electrical Engineering and Computer Engineering, Aerospace Engineering, Software Engineering, Imaging Science, Optical Engineering, Applied Mathematics, Physics, Astronomy, Astrophysics, Computer Science or a related discipline.
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Technical expertise with data models , data mining , and segmentation techniques. Experience with AWS cloud services : EC2 , EMR, RDS, Redshift , Modern data platforms, Snowflake , dbt , Fivetran and Airflow.
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For consideration, applicants must have his or her Bachelor's Degree in clinical laboratory science, biomedical science, medical technology or in a life/biological science in addition to either ASCP or AMT Certification as a Medical Technologist (MT)/ Medical Laboratory Scientist (MLS.
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Preferred Skills Production experience with core data platforms such as SQL Server, Databricks, Azure, Spark, and Hadoop. Hands-on knowledge of Cloud and Distributed Data Storage, including expertise in HDFS and ADLS. Strong understanding of data integration technologies, including Spark, Kafka, eventing/streaming, and Azure DataFactory.
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Expertise in at least one of the following domains: affective neuroscience, cognitive science, deep learning, and advanced analysis of fMRI data (e.g., encoding and decoding models) A doctoral degree or equivalent in an appropriate field (e.g., neuroscience, psychology, computer science, machine learning, or engineering.
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