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Data engineering utilities like but not limited to Apache spark, Kafka, Hadoop. Bachelor's or Master's degree in Data Engineering, Computer Science, Data Science, or a related field.
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Ability to ideate the data science projects lead the teams to deliver. Proven working Experience on GCP BQ, SQL, Hadoop, and machine learning. Strong experience in data mining, analysis, and handling of large structured and unstructured data.
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In Big Data, Hadoop, Spark, Kafka, BI, Data Warehousing, Data Science, Data Management, Data Storage, Data Visualization. Act as Data Technology Consultant and/or Data Solution Architect, working with the delivery team in various sized complex programs.
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Design, develop, and implement solutions for sanctions screening applications using technologies such as Unix, Oracle, MQ, Big Data - Hadoop, AWS, Databricks etc. We provide investment servicing, data & analytics, investment research & trading and investment management to institutional clients.
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Requires a Bachelor's degree in Computer Science, Mathematics, or related disciplines; 5-7 years experience in predictive analytics and experience with software such as Hadoop technologies; 5-7 years Teradata experience and complex SQL, or equivalent; or any combination of education and experience which would provide an equivalent background.
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Bioinformatics, computational biology, Data Science, Machine Learning, LIMS, Software Engineering, Genomics, Artificial Intelligence, NGS, Deep Learning, NLP, Life Sciences, Biotechnology, Personalized Medicine, Diversity, Equity and Inclusion Recruiting, and DEIB services.
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Understanding of data engineering best practices related to architecture patterns supporting varying data types, volume, and velocity. 10+ years of software design and development experience using Python, PySpark/Hadoop, Pandas, NumPy, SciPy, Jupyter notebook etc.
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Familiarity with big data processing tools (e.g., Hadoop, Spark) is advantageous. Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
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To that end, we seek qualified data science candidates interested in applying their skills to organizational and educational assessment challenges. Are you interested in using innovative data science to help make decisions in high-stakes assessment settings affecting individual employees, students, members of the military, and credentialed professionals.
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2 - 4 years of hands-on marketing analytics experience in a professional environment or 1+ years with an advanced degree in Marketing Science, Data Science, Statistics, Economics/Econometrics, Operations Research, Computer Science, or Engineering.
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Background in education, training or experience must include Python, SQL, Distributed computing platform/technology for data processing such as Hadoop or Hive, PySpark, Cloud Computation, ETL (Extract/Transform/Load.
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Some knowledge of big data tools like Spark, Hadoop, Kafka, etc. 5+ years of Data Engineer experience working with large datasets, data analysis, and a solid understanding of data science.
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Collaborate with senior engineers and data scientists to understand project requirements and develop machine learning models and algorithms. By providing intelligent and data-driven solutions, they strive to enhance the efficiency and effectiveness of the hiring process, ultimately helping companies find the best talent and individuals find their dream jobs.
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Proficiency with Linux, R, Python, or Java; expertise with versioning software (e.g., Git), big data solutions and data processing frameworks (e.g., Spark, Hadoop); At least six years of experience in Data Science or Modeling for consumer lending, two years of leadership experience in highly quantitative teams; Professional experience waived with at least four years of Data Science or Modeling experience and Ph. D. Degree in highly quantitative field (Statistics, Economics, Mathematics, or other quantitatively oriented degree.
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Applied knowledge of cloud and big data platform and tools (e.g., GCP, big-query, Hadoop, Python) You will work with analytics counterparts across data-science, business-intelligence, and insights to conceptualize and translate questions to actions and outcomes.
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