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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Our data science track covers most of the below: Topics and content might change based on the market requirements. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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5+ years hands-on experience with the Big Data stack (HDFS, SPARK, MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume, Kafka) Hands-on experience with "productionalizing" Big Data applications (e.g. administration, configuration management, monitoring, debugging, and performance tuning.
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Strong foundational understanding of Big Data ecosystems to make trade-off decisions while developing end to end solutions on Cloud/On-Prem/Hybrid Data tech stackExperience balancing new product development with maintaining day-to-day data reporting operations in a very large scale enterprise set upExperience applying both qualitative analysis and quantitative analysis techniques and familiarity with common data science models and approaches to problem-solving.
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3+ years of hands-on experience as a quantitative developer developing financial models and software solutions. Experience working with financial data sets like Factset and Bloomberg a plus.
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Required Skills: 10+ years professional work experience as a data scientist or on advanced analytics / statistics projects with 5+ years’ experience in one of the following sectors: Aerospace & Defense, Automotive, Banking, Consumer Products & Retail, Financial Services, Healthcare, High Tech, Industrial Products, Insurance, Life Sciences, Manufacturing, Public Sector, Telecom, Media & Entertainment, and Energy & Utilities.
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Ability to design cloud and on premise data solutions and provide guidance across storage, big data platform services, Big Data ecosystem, vendor SaaS integrations, RDBMS and NoSQL databases is a plus.
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Hands-on experience in developing scalable data pipeline using technologies like Kafka, Databricks, Spark and Scala applying ETL and ELT concepts. 3+ years of hands-on experience in implementing data lake systems using AWS/Azure cloud technologies such as S3, Databricks, Hive.
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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.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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Knowledge on AWS Lake Formation, AWS Glue Data Catalog and fine-grained access control. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more.
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Minimum THREE (3) years of hands-on experience implementing Collibra data catalog, data governance, data lineage, data privacy, and data quality capabilities.
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BS in Medical Technology, Clinical Laboratory Science or a chemical, physical, or biological science degree. Demonstrate proper communication skills to relate pertinent data or information about the patient or laboratory sample to appropriate care provider.
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You will own and be responsible for leading the product development lifecycle for services that support online and offline use cases, cross-domain and historical time-series data. PREFERRED QUALIFICATIONS- Experience working directly with Engineers on product enhancements- Experience in project management methodologies, business analysis, or process improvement- Experience owning data-centric products.
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In-depth knowledge on data engineering, DB models and architecture in RDBMS, Big Data and other cloud databases such as snowflake, Databricks, etc. Proven hands-on experience in Java, JEE, Streaming, API, Microservices, Containerization and UX/UI tools such as Angular JS/React, etc.
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data science big hands on financial services jobs Title: scientist in Newark, NJ
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