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Familiarity with Big Data technology in cloud and on-premises environments: Hadoop, HDFS, Spark, NoSQL Databases, Hive, MongoDB, Airflow, Kafka, AWS, Azure, Dockers or Snowflake. Familiarity with data visualization tools such as Tableau or Power BI.
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The Risk Data Scientist will use analytical skills to identify and prevent fraud & credit risks. You will own the key metrics, develop data pipelines, ETL. You will also make a direct impact on Square's priorities and Banking initiatives (primarily SQ’s debit card) by building risk detection strategies, developing & tracking key success metrics, influencing partners through data and enabling growth of the business.
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Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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Lead the CAs and audits for Prisma, Guardium, App Security and associated controls sustainability and prod supportLead organic modernization of legacy applications as well as build functional data expertise on vulnerability management and application security domains.
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We are looking for a Data Scientist to join our Risk Data team. Have a chance to use machine learning tools to develop data-driven solutions. Experience driving data-driven solutions and project-managing their implementation.
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Knowledge of data lake and data warehouse solutions, including Databricks, Snowflake, Amazon Redshift, Google BigQuery, Azure Data Factory, Airflow etc. Proven experience (8+) in a data engineering role, with expertise in designing and building data pipelines, ETL processes, and data warehouses.
ExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Build data pipelines and ETL processes using Google Cloud Dataflow, Apache Beam, and Google Cloud Dataprep. Manage and optimize BigQuery for data analysis and SQL queries. Proficiency in a programming language such as Python, Java, or Scala for data engineering tasks.
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Experience working with SQL DBMS systems (eg., SQL Server, Oracle, Redshift, Teradata)Experience in the data warehouse spaceSecurity, Stability, Reliability, Scalability, Fault Tolerance, Performance, Monitoring Compensation USA Compensation Range: $80,000 - $82,000 Additionally, the following benefits are provided by Red Ventures, subject to eligibility requirements.
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Work From Home, Entry Level Data Entry Clerk As A Research Participant. Data entry skills. This is a remote work from home part time gig, you'll need a computer, laptop or mobile device.
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The team comprises experts in data governance, data quality, and system integration, working together in a dynamic and supportive environment. 2+ years in master data management, preferably in global projects/companies.
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Big Data Architecture, Cloud Data Platforms Architecture (Azure, Databricks, Snowflake), In-house Big Data Platforms (Hadoop, Teradata, Exadata) This role provides you with a broad platform to build partnerships with business and risk counterparts, a vantage point to explore end-to-end data ecosystems and technologies, and ability to co-develop data solutions for GRM that drive the greatest value across the organization.
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Working knowledge in Data Management tools such as Collibra DQ, Alation, Tosca or others. Responsibilities will include data operations, analytics, and stewardship with the purpose of maintaining data quality and integrity in our platform.
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Knowledge of Statistics, SAS, Python, Computer Vision, data visualization tools. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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Eclaro International is currently recruiting for AML Data Quality Audit Manager for one of our financial services clients. s a member of the Data Quality (DQ) Audit team, the candidate will execute audit programs designed to measure and report on data risk across the enterprise.
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Experience in leading data science projects with a strong background in financial risk and deep learning. Assume a key role in thought leadership, utilizing your expertise to guide the organization's data strategy and establish a reputation as an industry expert in data science and analytics.
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Title: data Company: Cottonwood Financial Administrative Services in Charlotte, NC
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