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A minimum of 6 years of experience in designing and implementing complex AI and ML solutions, as a Senior Data scientist, Machine Learning Engineer, or AI Engineer. Knowledge and experience working with Spark or Databricks is a plus.
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CGI is seeking a Sr. Data Scientist to join our Emerging Technology Practice. Senior Data Scientist. Data warehouses and file stores such as Snowflake, RedShift, Teradata, BigQuery, Amazon S3, Amazon RDS, Azure Synapse, Databricks Lakehouse, etc.
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Experience of implementing Amazon EMR or Big Data technologies like Hadoop, Spark, Presto, Hive will be a plus. Implementation experience of Big Data technologies like Hadoop, Spark, Presto, Hive, and Hue will be a major advantage.
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Have experience with both proprietary and open-source big data technologies and platforms (Snowflake, Vertica, Hive, Spark, Presto, Airflow). Experience with streaming of data - Kafka or Kinesis and exposure to the AWS environment.
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Cert Histocompatibility Spec (CHS-ABHI), Cert Histocompatibility Techno (CHT-ABHI), Clinical Laboratory Scientist (CLS), HEW (HEW), Medical Laboratory Scientist (MLS), Medical Technologist (MT), Specialist in Cytology-ASCP (SCT), Specialist in Cytometry-ASCP (SCYM), Molecular Biology Spec-ASCP (SMB.
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Proficiency in at-least one of the following programming languages - Python, Scala or Java. Experience in multi-threaded, concurrent programming and synchronization Cloud technology experience on platforms like AWS, Microsoft Azure, Google Cloud Experience developing Big Data applications using java, Spark, Kafka is a huge plus.
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Design and implement distributed data processing pipelines using Spark, Hive, Python, Airflow, and other tools and languages prevalent in the Hadoop ecosystem. Explore and build proof of concepts using open source NOSQL technologies such as HBase, DynamoDB, Cassandra and Distributed Stream Processing frameworks like Apache Spark, Kafka stream.
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Small business with a 40-year history as a first-class materials science and applied research and development firm seeks a polymer scientist with experience in hands-on laboratory formulation and optimization of new, patentable, high performance polymer materials such as coatings, molding compounds, adhesives, resins, sealants, and foams.
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Conduct research in several projects, including RCRC, CRISPR screen analysis, disease genomics and functional data analysis, and immunotherapy data models. Engage in services involving data organization, analysis and visualization, including increased scope in data types to be analyzed: new data include CUT&RUN, CRISPR and single cell data.
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What you will likely bring:Strong experience in Microsoft Azure Proficiency in data processing frameworks such as Azure Spark, or cloud-native data processing services (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Synapse, Snowflake, CosmosDB) Experience with data integration and ETL (Extract, Transform, Load) processes, including tools like cloud-native orchestration services.
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Qualifications Bachelor’s or Master's degree in Computer Science, Statistics, Data Science, Artificial Intelligence, or a related field. Enterprise Cognitive Digital Assistant Services, and AI Service Desk. As an Enterprise ML Developer, we seek an expert in machine learning to help us extract value from our data.
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Experience with data warehouse and big data technologies such as Azure Synapse Analytics, Azure Data Lake Storage, Spark, Kafka, Databricks, and Containers. Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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In this role, you will play a vital role in analyzing and interpreting next-generation sequencing (NGS) data, contributing to the success of our client projects from initial data exploration to actionable insights.
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As an integral part of our team, you will not only need to tackle operational challenges at every layer of the system infrastructure, but also set up essential tools like Spark, Databricks, Snowflake, Kubernetes, and Kafka for data science infrastructure.
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Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink. Data Processing Frameworks: Lead the implementation and optimization of data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
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