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Experience working with modern data engineering tech stack and platforms (Databricks, Snowflake, AWS Services, DBT) Experience working with real-time data streams processing and ingestion frameworks ( Apache Kafka, Kinesis, Flink or Spark Structured Streaming.
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Experience with SharePoint Syntex / AI Builder, Snowflake, MLFlow, Forms Recognizer, Power Automate, Databricks, Azure SQL, Cognitive Services, and Azure ML.Strong understanding of data architecture principles.
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Minimum one year of experience implementing modern applications using Cloud Based Solutions/ Technologies (AWS Redshift, S3, Google BigQuery, Azure Data Bricks, Synapse) preferred. Strong knowledge and experience in cloud data warehousing solutions (i.e. BigQuery, Snowflake, Synapse.
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Experience managing information security technologies such as IDS/IPS, SIEM, endpoint detection & response, DLP, data encryption, proxies, and network access control, as well as security policies and procedures, and incident response.
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The successful Architect will be able to drive high priority data initiatives using AWS, Databricks, and Snowflake. Experience with DevOps, and DataOps (GitHub Actions, Terraform, Azure DevOps, data governance tools) are a plus.
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In this role specifical, the Principal Data Scientist (Deep Learning) will lead algorithmic solution design, rapid prototyping, and technical review for the ML/AI models underlying personalized user experiences and content promotion.
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Micro-batch streaming and continuous streaming process in Databricks for high latency, low latency and ultra-low latency of data accordingly by using inbuilt Apache spark modules. Strong hands-on expertise in building Data engineering solutions using Apache Spark and Scala.
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5+ years of working experience as Statistician, Data Analyst, Machine Learning Engineer, Data Scientist in digital marketing, advertising, healthcare, or other areas requiring customer level predictive analytics.
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Experience with data visualization (e.g., R Shiny, Tableau, Spotfire). Experience with data wrangling, data matching, and ETL techniques while programming in several languages (Python, R, SQL, and Spark) to extract and transform data from a variety of data sources (Oracle, SQL, Hadoop.
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Implement row level security on data using the application security layer models in Microsoft Power BI. TITLE – Power BI Data Visualization Developer. Hands on experience with developing and optimizing complex SQL queries to manipulate data for Business Intelligence.
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Our products focus on data and analytics in structured finance (CMBS), collateralized loan obligations (CLO), commercial real estate (CRE), and banking & lending. A drive to work on financial data systems & pipelines including experience working with structured finance or commercial real estate datasets.
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Experienced with data analysis/data review and visualization tool sets including but not limited to Python, R, Spotfire, SAS. In-depth knowledge of the drug development process and its impact on data quality, in particular risk-based approach, biometrics procedures, workflows.
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Both the Data Science Platform and BQuant are solutions that aim to provide scalable compute, specialized hardware and first-class support for a variety of workloads such as Spark, PyTorch and Jupyter.
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Perform quality control and debugging assistance for junior data scientists. Structure and perform quality control procedures for data ingestion, querying, and usages. Perform exploratory data analysis and render key insights through evidenced results.
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Job Overview: A law firm based in New York City, NY, is seeking a passionate and self-motivated Cyber, Privacy, And Data Innovation Litigation Associate Attorney with 3-5 years of experience to join its team.
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Title: data Company: Ceribell in Jericho, NY
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