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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake,Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar.
$94,500 - $122,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience in writing complex SQL queries, and high-performance, reliable and maintainable code; Experience with Python development for data analysis and data modeling; Experience with Hadoop, including Hive, Spark, Impala, Pig, and Oozie; and Experience with AWS/Cloud components, including EC2, S3, and EMR.
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PREFERRED SKILLS Experience with databases, such as SQL Server, AWS RDS, DynamoDB. Experience with Convolutional Neural Networks (CNNs) Experience solving streaming and batch data processing problems at scale.
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Some exposure to Big Data technologies, Apache Spark, AWS, AWS S3, amazon Glue, cloud -based data architecture is preferred. Qualifications Bachelor’s degree in computer science, Data Science, or data engineering 3-5 years of experience as a Data Analyst with exposure to data governance practices.
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Our people extend into all industries we conduct work with our clients in the areas of; data science, data engineering, data strategy, intelligent process automation, data ecosystems, intelligent industry/IoT, enterprise management, customer-first marketing, and data partnerships/disruptors (such as SAP, Microsoft, Google, AWS, Snowflake, Oracle, Adobe, etc.
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Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark, Kafka). Relevant certifications in data management or related areas (e.g., Certified Data Management Professional, AWS Certified Big Data - Specialty) are a plus.
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Warehousing: Experience in Snowflake Data Cloud, SQL Server, Azure, AWS Redshift, Google Big Query. Science & programming: Python, R, SQL, SAS, Java or similar ß Lower Priority.
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Experience with Microsoft Azure, Google BigQuery and/or AWS cloud platforms. 4+ years of experience with scientific scripting languages (e.g., Python, R, SAS), as well as big data frameworks such as Hadoop MapReduce.
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Experience with big data technologies (e.g., Hadoop, Spark, Databricks, Snowflake) and cloud platforms (e.g., AWS, Azure). As a Senior Manager within Axtrias Data Science COE you will have the responsibility to apply AI/GenAI and data science to solve business problems for functional areas within Biopharma/Oncology, relating to Sales and Marketing, Medical Affairs and/or Clinical.
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This role will be part of a dedicated hybrid actuarial/data science team designing and delivering powerful analytical tools utilizing statistical modeling, machine learning, cloud computing, and big data platforms to enhance or overhaul core actuarial processes.
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Bachelor’s degree in Computer Science, Engineering, IT, MIS, or a related disciplineExpertise in Python, SQL, and RExpertise in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON Expertise in ETL concerning metadata management and data validation Expertise in Unix and Git Expertise in Automation tools (Autosys, Cron, Airflow, etc.
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Experience with AWS Services (i.e. S3, EMR, etc) a plus Experience with Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus. Lead the use and development of GitHub best practices for version control, documentation, and code collaboration throughout the data science lifecycle and ensure solutions align with best practices.
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One of the following AWS Certifications: AWS Certified Cloud Practitioner AWS Certified SysOps Administrator (Associate) AWS Certified DevOps Engineer (Professional) AWS Certified Big Data (Specialty) Experience utilizing AGILE development methodologies and Application Lifecycle Management.
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Familiarity with big data processing and cloud computing will be critical to succeed in this environment. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI will be a bonus.
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Experience building AWS cloud data solutions and migrating from on-prem to cloudExperience leading, managing and delivering complex cloud-based architecture engagements end-to-end with resources in multiple locationsHands-on experience with big data application development and/or with cloud data warehousing (e.g. Spark, Redshift, Snowflake, Azure SQL DW, BigQuery)Strong communication skills and a working knowledge of agile development, including DevOps concepts.
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