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The Biomedical Data Analyst will be responsible for working directly with the HPV Serology Laboratory to manage large datasets and conduct data analyses of immunological data, including serology assay data, flow cytometry and other data generated by the laboratory in support of large clinical and epidemiological studies.
Full-timeExpandUpdated 29 days ago - UpvoteDownvoteShare Job
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We’re looking for a Data Scientist/Sr. Data Scientist for Marketing Analytics with a passion to work with the marketing team to help measure the effectiveness of marketing initiatives across geographies and lead insight generation to inform our marketing investments.
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Cloud and Data Solutions : Experience in building cloud-based Data Warehouse/Data Lake solutions (AWS Athena, Redshift, Snowflake) and familiarity with AWS cloud services and infrastructure-as-code tools (CDK, Terraform.
$165,000 - $206,000 a yearFull-timeExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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The Homeless Management Information System Data Coordinator (HMIS) is responsible for all HMIS data entry daily and overall management of HMIS system, records, and filing for The Traditional SSVF and SSVF Shallow Subsidy programs’ demographic information of all veterans’ service by these programs.
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DataBricks, Azure Data Factory, Python, SQL, Data Lake Architecture, Azure DevOps Repos/ Git. (Azure Data Factory, Azure SQL, Azure Data Lake, Databricks). Summary: As a senior data engineer you will be responsible for loading and transforming data within the Data Lake environment while ensuring data quality and consistency.
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You have 8+ years of industry experience and proficiency in building distributed data pipelines for both batch and real-time (experience with Databricks, Spark, Hive, Iceberg, Kafka, Snowflake is helpful, but not strictly required.
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Responsibilities: Serves as Data Steward dedicated to health care payer Claims data operations & initiatives Works collaboratively with other enterprise and business data stewards to align standards and share best practices; represents Claims data domain in enterprise workgroups and data steward communities of practice Leads Data Governance initiatives and collaborations with business and IT operational stakeholders to: ○ Document, define, maintain, and manage data standards and assets.
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Strong proficiency in building and optimizing big data pipelines using Databricks Delta and Apache Spark. Proven experience as a Solution Architect or Data Engineer, with a focus on Databricks.
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Conduct in-depth data analysis using Python, MATLAB, and relevant tools to address complex problems, define key performance indicators for autonomous vehicle systems, and effectively communicate analytical insights to stakeholders.
$168,000 - $252,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Keywords : GCP, Google Cloud Platform, BigQuery, Composer, SQL, Python, Data Engineering, Data Pipelines. Experience working with Airflow as workflow management tools and build operators to connect, extract and ingest data as needed.
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Experience programming and reviewing code using statistical and data software tools like R, Python, SQL, Spark, Scala, etc. Degree must be earned in a related field such as statistics, data science, applied mathematics, computer science, information systems, or other quantitative and computational discipline.
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Proficiently uses statistical programming languages and tools appropriate for data science domains. Experience successfully using Big Data technologies like Hadoop, Spark, Hive, NoSQL, in-memory data stores, etc., and Cloud technologies such as AWS, Azure, etc.
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Understanding of data governance and metadata management tools that may be used in DoD projects, such as Collibra or Informatica Axon. Proficiency in data modeling tools such as Erwin Data Modeler, IBM Data Architect, or Oracle SQL Developer Data Modeler for creating and maintaining data models.
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Proficiency with GCP data services (BigQuery; Dataflow; Data Fusion; Dataproc; Cloud Composer; Pub/Sub; Google Cloud Storage). Experience with data governance (data plex), data security, and compliance best practices on GCP.
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This architecture includes an Databricks, Microsoft Azure platform tools (including Data Lake, Synapse), Apache platform tools (including Hadoop, Hive, Impala, Spark, Sedona, Airflow) and data pipeline/ETL development tools (including Streamsets, Apache NiFi, Azure Data Factory.
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